Vidyalankar final-essentials of communication systems

61
Essentials Of Communication Systems A Presentation By- A. S. Kurhekar http://sites.google.com/site/anilkurhekar100

description

Fundamentals of communication systems

Transcript of Vidyalankar final-essentials of communication systems

Page 1: Vidyalankar final-essentials of communication systems

Essentials Of Communication Systems

A Presentation By-A S Kurhekar

httpsitesgooglecomsiteanilkurhekar100

Overview of Analog Technology

Areas of ApplicationOld telephone networksMost television broadcasting at presentRadio broadcasting

Analog Signals The Basics

Cycle

Time

Signal

Amplitude

Frequency = CyclesSecond

Amplitude and Cycle

Amplitude Distance above reference line

Cycle One complete wave

Frequency Frequency

Cycles per second Hertz is the unit used for expressing frequency

Frequency spectrum Defines the bandwidth for different analog

communication technologies

Frequency Spectrumand Bandwidth Available range of frequencies for

communication Starts from low frequency communication

such as voice and progresses to high frequency communication such as satellite communication

The spectrum spans the entire bandwidth of communicable frequencies

Frequency Spectrum

Low Frequency High Frequency

Radio Frequency

CoaxialCable

MHz

Voice

KHz

SatelliteTransmission

MicrowaveMHz

Low-endVoice band

MiddleMicrowave

High-endSatellite communication

An Overview of Digital Technology

Areas of Application Computers New telephone networks Phased introduction of digital television technology

Digital Technology Basics Digital signals that could be assigned digital values

Digital computer technology Digital signals Binary representation

Encoded into ones and zeros

Digital Signal And Binary Signals

Digital signals Value limited to a finite set Digital systems more robust Binary Signals Has at most 2 values Used to represent bit values Bit time T needed to send 1 bit Data rate R=1T bits per second

t

x(t)

t

x(t) 1

0 0 0

1 1

0T

Digital Terms

Pulse Pulse duration Pulse amplitude Signal strength

Clock Speed and Execution Speed Pulse duration is inversely proportional to the

clock frequency Faster the clock speed the smaller the pulse

duration Smaller the pulse duration the faster the

execution in general

Performance Metrics

Analog Communication Systems Metric is fidelity Want m(t)m(t)

Digital Communication Systems Metrics are data rate (R bps) and probability of

bit error (Pb=p(bb)) Without noise never make bit errors With noise Pb depends on signal and noise

power data rate and channel characteristics

Data Rate Limits

Data rate R limited by signal power noise power distortion and bit error probability

Without distortion or noise can have infinite data rate with Pb=0

Shannon capacity defines maximum possible data rate for systems with noise and distortion Rate achieved with bit error probability close to zero In white Gaussian noise channels C=B log(1+SNR) Does not show how to design real systems

Shannon obtained C=32 Kbps for phone channels Get higher rates with modemsDSL (use more BW) Nowhere near capacity in wireless systems

Signal Energy and Power The energy in a signal g(t) is

The power in a signal g(t) is

Power is often expression in dBw or dBm [10 log10 P] dBW is dB power relative to Watts [10 log10 (P001)] dBm is dB power relative to mWatts Signal powerenergy determines its resistance to noise

dttgdttgEg )(|)(| 2

T

T

T

T

T

T dttgT

dttgT

P 22 )(2

1lim|)(|

2

1lim

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 2: Vidyalankar final-essentials of communication systems

Overview of Analog Technology

Areas of ApplicationOld telephone networksMost television broadcasting at presentRadio broadcasting

Analog Signals The Basics

Cycle

Time

Signal

Amplitude

Frequency = CyclesSecond

Amplitude and Cycle

Amplitude Distance above reference line

Cycle One complete wave

Frequency Frequency

Cycles per second Hertz is the unit used for expressing frequency

Frequency spectrum Defines the bandwidth for different analog

communication technologies

Frequency Spectrumand Bandwidth Available range of frequencies for

communication Starts from low frequency communication

such as voice and progresses to high frequency communication such as satellite communication

The spectrum spans the entire bandwidth of communicable frequencies

Frequency Spectrum

Low Frequency High Frequency

Radio Frequency

CoaxialCable

MHz

Voice

KHz

SatelliteTransmission

MicrowaveMHz

Low-endVoice band

MiddleMicrowave

High-endSatellite communication

An Overview of Digital Technology

Areas of Application Computers New telephone networks Phased introduction of digital television technology

Digital Technology Basics Digital signals that could be assigned digital values

Digital computer technology Digital signals Binary representation

Encoded into ones and zeros

Digital Signal And Binary Signals

Digital signals Value limited to a finite set Digital systems more robust Binary Signals Has at most 2 values Used to represent bit values Bit time T needed to send 1 bit Data rate R=1T bits per second

t

x(t)

t

x(t) 1

0 0 0

1 1

0T

Digital Terms

Pulse Pulse duration Pulse amplitude Signal strength

Clock Speed and Execution Speed Pulse duration is inversely proportional to the

clock frequency Faster the clock speed the smaller the pulse

duration Smaller the pulse duration the faster the

execution in general

Performance Metrics

Analog Communication Systems Metric is fidelity Want m(t)m(t)

Digital Communication Systems Metrics are data rate (R bps) and probability of

bit error (Pb=p(bb)) Without noise never make bit errors With noise Pb depends on signal and noise

power data rate and channel characteristics

Data Rate Limits

Data rate R limited by signal power noise power distortion and bit error probability

Without distortion or noise can have infinite data rate with Pb=0

Shannon capacity defines maximum possible data rate for systems with noise and distortion Rate achieved with bit error probability close to zero In white Gaussian noise channels C=B log(1+SNR) Does not show how to design real systems

Shannon obtained C=32 Kbps for phone channels Get higher rates with modemsDSL (use more BW) Nowhere near capacity in wireless systems

Signal Energy and Power The energy in a signal g(t) is

The power in a signal g(t) is

Power is often expression in dBw or dBm [10 log10 P] dBW is dB power relative to Watts [10 log10 (P001)] dBm is dB power relative to mWatts Signal powerenergy determines its resistance to noise

dttgdttgEg )(|)(| 2

T

T

T

T

T

T dttgT

dttgT

P 22 )(2

1lim|)(|

2

1lim

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 3: Vidyalankar final-essentials of communication systems

Analog Signals The Basics

Cycle

Time

Signal

Amplitude

Frequency = CyclesSecond

Amplitude and Cycle

Amplitude Distance above reference line

Cycle One complete wave

Frequency Frequency

Cycles per second Hertz is the unit used for expressing frequency

Frequency spectrum Defines the bandwidth for different analog

communication technologies

Frequency Spectrumand Bandwidth Available range of frequencies for

communication Starts from low frequency communication

such as voice and progresses to high frequency communication such as satellite communication

The spectrum spans the entire bandwidth of communicable frequencies

Frequency Spectrum

Low Frequency High Frequency

Radio Frequency

CoaxialCable

MHz

Voice

KHz

SatelliteTransmission

MicrowaveMHz

Low-endVoice band

MiddleMicrowave

High-endSatellite communication

An Overview of Digital Technology

Areas of Application Computers New telephone networks Phased introduction of digital television technology

Digital Technology Basics Digital signals that could be assigned digital values

Digital computer technology Digital signals Binary representation

Encoded into ones and zeros

Digital Signal And Binary Signals

Digital signals Value limited to a finite set Digital systems more robust Binary Signals Has at most 2 values Used to represent bit values Bit time T needed to send 1 bit Data rate R=1T bits per second

t

x(t)

t

x(t) 1

0 0 0

1 1

0T

Digital Terms

Pulse Pulse duration Pulse amplitude Signal strength

Clock Speed and Execution Speed Pulse duration is inversely proportional to the

clock frequency Faster the clock speed the smaller the pulse

duration Smaller the pulse duration the faster the

execution in general

Performance Metrics

Analog Communication Systems Metric is fidelity Want m(t)m(t)

Digital Communication Systems Metrics are data rate (R bps) and probability of

bit error (Pb=p(bb)) Without noise never make bit errors With noise Pb depends on signal and noise

power data rate and channel characteristics

Data Rate Limits

Data rate R limited by signal power noise power distortion and bit error probability

Without distortion or noise can have infinite data rate with Pb=0

Shannon capacity defines maximum possible data rate for systems with noise and distortion Rate achieved with bit error probability close to zero In white Gaussian noise channels C=B log(1+SNR) Does not show how to design real systems

Shannon obtained C=32 Kbps for phone channels Get higher rates with modemsDSL (use more BW) Nowhere near capacity in wireless systems

Signal Energy and Power The energy in a signal g(t) is

The power in a signal g(t) is

Power is often expression in dBw or dBm [10 log10 P] dBW is dB power relative to Watts [10 log10 (P001)] dBm is dB power relative to mWatts Signal powerenergy determines its resistance to noise

dttgdttgEg )(|)(| 2

T

T

T

T

T

T dttgT

dttgT

P 22 )(2

1lim|)(|

2

1lim

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 4: Vidyalankar final-essentials of communication systems

Amplitude and Cycle

Amplitude Distance above reference line

Cycle One complete wave

Frequency Frequency

Cycles per second Hertz is the unit used for expressing frequency

Frequency spectrum Defines the bandwidth for different analog

communication technologies

Frequency Spectrumand Bandwidth Available range of frequencies for

communication Starts from low frequency communication

such as voice and progresses to high frequency communication such as satellite communication

The spectrum spans the entire bandwidth of communicable frequencies

Frequency Spectrum

Low Frequency High Frequency

Radio Frequency

CoaxialCable

MHz

Voice

KHz

SatelliteTransmission

MicrowaveMHz

Low-endVoice band

MiddleMicrowave

High-endSatellite communication

An Overview of Digital Technology

Areas of Application Computers New telephone networks Phased introduction of digital television technology

Digital Technology Basics Digital signals that could be assigned digital values

Digital computer technology Digital signals Binary representation

Encoded into ones and zeros

Digital Signal And Binary Signals

Digital signals Value limited to a finite set Digital systems more robust Binary Signals Has at most 2 values Used to represent bit values Bit time T needed to send 1 bit Data rate R=1T bits per second

t

x(t)

t

x(t) 1

0 0 0

1 1

0T

Digital Terms

Pulse Pulse duration Pulse amplitude Signal strength

Clock Speed and Execution Speed Pulse duration is inversely proportional to the

clock frequency Faster the clock speed the smaller the pulse

duration Smaller the pulse duration the faster the

execution in general

Performance Metrics

Analog Communication Systems Metric is fidelity Want m(t)m(t)

Digital Communication Systems Metrics are data rate (R bps) and probability of

bit error (Pb=p(bb)) Without noise never make bit errors With noise Pb depends on signal and noise

power data rate and channel characteristics

Data Rate Limits

Data rate R limited by signal power noise power distortion and bit error probability

Without distortion or noise can have infinite data rate with Pb=0

Shannon capacity defines maximum possible data rate for systems with noise and distortion Rate achieved with bit error probability close to zero In white Gaussian noise channels C=B log(1+SNR) Does not show how to design real systems

Shannon obtained C=32 Kbps for phone channels Get higher rates with modemsDSL (use more BW) Nowhere near capacity in wireless systems

Signal Energy and Power The energy in a signal g(t) is

The power in a signal g(t) is

Power is often expression in dBw or dBm [10 log10 P] dBW is dB power relative to Watts [10 log10 (P001)] dBm is dB power relative to mWatts Signal powerenergy determines its resistance to noise

dttgdttgEg )(|)(| 2

T

T

T

T

T

T dttgT

dttgT

P 22 )(2

1lim|)(|

2

1lim

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 5: Vidyalankar final-essentials of communication systems

Frequency Spectrumand Bandwidth Available range of frequencies for

communication Starts from low frequency communication

such as voice and progresses to high frequency communication such as satellite communication

The spectrum spans the entire bandwidth of communicable frequencies

Frequency Spectrum

Low Frequency High Frequency

Radio Frequency

CoaxialCable

MHz

Voice

KHz

SatelliteTransmission

MicrowaveMHz

Low-endVoice band

MiddleMicrowave

High-endSatellite communication

An Overview of Digital Technology

Areas of Application Computers New telephone networks Phased introduction of digital television technology

Digital Technology Basics Digital signals that could be assigned digital values

Digital computer technology Digital signals Binary representation

Encoded into ones and zeros

Digital Signal And Binary Signals

Digital signals Value limited to a finite set Digital systems more robust Binary Signals Has at most 2 values Used to represent bit values Bit time T needed to send 1 bit Data rate R=1T bits per second

t

x(t)

t

x(t) 1

0 0 0

1 1

0T

Digital Terms

Pulse Pulse duration Pulse amplitude Signal strength

Clock Speed and Execution Speed Pulse duration is inversely proportional to the

clock frequency Faster the clock speed the smaller the pulse

duration Smaller the pulse duration the faster the

execution in general

Performance Metrics

Analog Communication Systems Metric is fidelity Want m(t)m(t)

Digital Communication Systems Metrics are data rate (R bps) and probability of

bit error (Pb=p(bb)) Without noise never make bit errors With noise Pb depends on signal and noise

power data rate and channel characteristics

Data Rate Limits

Data rate R limited by signal power noise power distortion and bit error probability

Without distortion or noise can have infinite data rate with Pb=0

Shannon capacity defines maximum possible data rate for systems with noise and distortion Rate achieved with bit error probability close to zero In white Gaussian noise channels C=B log(1+SNR) Does not show how to design real systems

Shannon obtained C=32 Kbps for phone channels Get higher rates with modemsDSL (use more BW) Nowhere near capacity in wireless systems

Signal Energy and Power The energy in a signal g(t) is

The power in a signal g(t) is

Power is often expression in dBw or dBm [10 log10 P] dBW is dB power relative to Watts [10 log10 (P001)] dBm is dB power relative to mWatts Signal powerenergy determines its resistance to noise

dttgdttgEg )(|)(| 2

T

T

T

T

T

T dttgT

dttgT

P 22 )(2

1lim|)(|

2

1lim

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 6: Vidyalankar final-essentials of communication systems

Frequency Spectrum

Low Frequency High Frequency

Radio Frequency

CoaxialCable

MHz

Voice

KHz

SatelliteTransmission

MicrowaveMHz

Low-endVoice band

MiddleMicrowave

High-endSatellite communication

An Overview of Digital Technology

Areas of Application Computers New telephone networks Phased introduction of digital television technology

Digital Technology Basics Digital signals that could be assigned digital values

Digital computer technology Digital signals Binary representation

Encoded into ones and zeros

Digital Signal And Binary Signals

Digital signals Value limited to a finite set Digital systems more robust Binary Signals Has at most 2 values Used to represent bit values Bit time T needed to send 1 bit Data rate R=1T bits per second

t

x(t)

t

x(t) 1

0 0 0

1 1

0T

Digital Terms

Pulse Pulse duration Pulse amplitude Signal strength

Clock Speed and Execution Speed Pulse duration is inversely proportional to the

clock frequency Faster the clock speed the smaller the pulse

duration Smaller the pulse duration the faster the

execution in general

Performance Metrics

Analog Communication Systems Metric is fidelity Want m(t)m(t)

Digital Communication Systems Metrics are data rate (R bps) and probability of

bit error (Pb=p(bb)) Without noise never make bit errors With noise Pb depends on signal and noise

power data rate and channel characteristics

Data Rate Limits

Data rate R limited by signal power noise power distortion and bit error probability

Without distortion or noise can have infinite data rate with Pb=0

Shannon capacity defines maximum possible data rate for systems with noise and distortion Rate achieved with bit error probability close to zero In white Gaussian noise channels C=B log(1+SNR) Does not show how to design real systems

Shannon obtained C=32 Kbps for phone channels Get higher rates with modemsDSL (use more BW) Nowhere near capacity in wireless systems

Signal Energy and Power The energy in a signal g(t) is

The power in a signal g(t) is

Power is often expression in dBw or dBm [10 log10 P] dBW is dB power relative to Watts [10 log10 (P001)] dBm is dB power relative to mWatts Signal powerenergy determines its resistance to noise

dttgdttgEg )(|)(| 2

T

T

T

T

T

T dttgT

dttgT

P 22 )(2

1lim|)(|

2

1lim

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 7: Vidyalankar final-essentials of communication systems

An Overview of Digital Technology

Areas of Application Computers New telephone networks Phased introduction of digital television technology

Digital Technology Basics Digital signals that could be assigned digital values

Digital computer technology Digital signals Binary representation

Encoded into ones and zeros

Digital Signal And Binary Signals

Digital signals Value limited to a finite set Digital systems more robust Binary Signals Has at most 2 values Used to represent bit values Bit time T needed to send 1 bit Data rate R=1T bits per second

t

x(t)

t

x(t) 1

0 0 0

1 1

0T

Digital Terms

Pulse Pulse duration Pulse amplitude Signal strength

Clock Speed and Execution Speed Pulse duration is inversely proportional to the

clock frequency Faster the clock speed the smaller the pulse

duration Smaller the pulse duration the faster the

execution in general

Performance Metrics

Analog Communication Systems Metric is fidelity Want m(t)m(t)

Digital Communication Systems Metrics are data rate (R bps) and probability of

bit error (Pb=p(bb)) Without noise never make bit errors With noise Pb depends on signal and noise

power data rate and channel characteristics

Data Rate Limits

Data rate R limited by signal power noise power distortion and bit error probability

Without distortion or noise can have infinite data rate with Pb=0

Shannon capacity defines maximum possible data rate for systems with noise and distortion Rate achieved with bit error probability close to zero In white Gaussian noise channels C=B log(1+SNR) Does not show how to design real systems

Shannon obtained C=32 Kbps for phone channels Get higher rates with modemsDSL (use more BW) Nowhere near capacity in wireless systems

Signal Energy and Power The energy in a signal g(t) is

The power in a signal g(t) is

Power is often expression in dBw or dBm [10 log10 P] dBW is dB power relative to Watts [10 log10 (P001)] dBm is dB power relative to mWatts Signal powerenergy determines its resistance to noise

dttgdttgEg )(|)(| 2

T

T

T

T

T

T dttgT

dttgT

P 22 )(2

1lim|)(|

2

1lim

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 8: Vidyalankar final-essentials of communication systems

Digital Signal And Binary Signals

Digital signals Value limited to a finite set Digital systems more robust Binary Signals Has at most 2 values Used to represent bit values Bit time T needed to send 1 bit Data rate R=1T bits per second

t

x(t)

t

x(t) 1

0 0 0

1 1

0T

Digital Terms

Pulse Pulse duration Pulse amplitude Signal strength

Clock Speed and Execution Speed Pulse duration is inversely proportional to the

clock frequency Faster the clock speed the smaller the pulse

duration Smaller the pulse duration the faster the

execution in general

Performance Metrics

Analog Communication Systems Metric is fidelity Want m(t)m(t)

Digital Communication Systems Metrics are data rate (R bps) and probability of

bit error (Pb=p(bb)) Without noise never make bit errors With noise Pb depends on signal and noise

power data rate and channel characteristics

Data Rate Limits

Data rate R limited by signal power noise power distortion and bit error probability

Without distortion or noise can have infinite data rate with Pb=0

Shannon capacity defines maximum possible data rate for systems with noise and distortion Rate achieved with bit error probability close to zero In white Gaussian noise channels C=B log(1+SNR) Does not show how to design real systems

Shannon obtained C=32 Kbps for phone channels Get higher rates with modemsDSL (use more BW) Nowhere near capacity in wireless systems

Signal Energy and Power The energy in a signal g(t) is

The power in a signal g(t) is

Power is often expression in dBw or dBm [10 log10 P] dBW is dB power relative to Watts [10 log10 (P001)] dBm is dB power relative to mWatts Signal powerenergy determines its resistance to noise

dttgdttgEg )(|)(| 2

T

T

T

T

T

T dttgT

dttgT

P 22 )(2

1lim|)(|

2

1lim

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 9: Vidyalankar final-essentials of communication systems

Digital Terms

Pulse Pulse duration Pulse amplitude Signal strength

Clock Speed and Execution Speed Pulse duration is inversely proportional to the

clock frequency Faster the clock speed the smaller the pulse

duration Smaller the pulse duration the faster the

execution in general

Performance Metrics

Analog Communication Systems Metric is fidelity Want m(t)m(t)

Digital Communication Systems Metrics are data rate (R bps) and probability of

bit error (Pb=p(bb)) Without noise never make bit errors With noise Pb depends on signal and noise

power data rate and channel characteristics

Data Rate Limits

Data rate R limited by signal power noise power distortion and bit error probability

Without distortion or noise can have infinite data rate with Pb=0

Shannon capacity defines maximum possible data rate for systems with noise and distortion Rate achieved with bit error probability close to zero In white Gaussian noise channels C=B log(1+SNR) Does not show how to design real systems

Shannon obtained C=32 Kbps for phone channels Get higher rates with modemsDSL (use more BW) Nowhere near capacity in wireless systems

Signal Energy and Power The energy in a signal g(t) is

The power in a signal g(t) is

Power is often expression in dBw or dBm [10 log10 P] dBW is dB power relative to Watts [10 log10 (P001)] dBm is dB power relative to mWatts Signal powerenergy determines its resistance to noise

dttgdttgEg )(|)(| 2

T

T

T

T

T

T dttgT

dttgT

P 22 )(2

1lim|)(|

2

1lim

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 10: Vidyalankar final-essentials of communication systems

Performance Metrics

Analog Communication Systems Metric is fidelity Want m(t)m(t)

Digital Communication Systems Metrics are data rate (R bps) and probability of

bit error (Pb=p(bb)) Without noise never make bit errors With noise Pb depends on signal and noise

power data rate and channel characteristics

Data Rate Limits

Data rate R limited by signal power noise power distortion and bit error probability

Without distortion or noise can have infinite data rate with Pb=0

Shannon capacity defines maximum possible data rate for systems with noise and distortion Rate achieved with bit error probability close to zero In white Gaussian noise channels C=B log(1+SNR) Does not show how to design real systems

Shannon obtained C=32 Kbps for phone channels Get higher rates with modemsDSL (use more BW) Nowhere near capacity in wireless systems

Signal Energy and Power The energy in a signal g(t) is

The power in a signal g(t) is

Power is often expression in dBw or dBm [10 log10 P] dBW is dB power relative to Watts [10 log10 (P001)] dBm is dB power relative to mWatts Signal powerenergy determines its resistance to noise

dttgdttgEg )(|)(| 2

T

T

T

T

T

T dttgT

dttgT

P 22 )(2

1lim|)(|

2

1lim

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 11: Vidyalankar final-essentials of communication systems

Data Rate Limits

Data rate R limited by signal power noise power distortion and bit error probability

Without distortion or noise can have infinite data rate with Pb=0

Shannon capacity defines maximum possible data rate for systems with noise and distortion Rate achieved with bit error probability close to zero In white Gaussian noise channels C=B log(1+SNR) Does not show how to design real systems

Shannon obtained C=32 Kbps for phone channels Get higher rates with modemsDSL (use more BW) Nowhere near capacity in wireless systems

Signal Energy and Power The energy in a signal g(t) is

The power in a signal g(t) is

Power is often expression in dBw or dBm [10 log10 P] dBW is dB power relative to Watts [10 log10 (P001)] dBm is dB power relative to mWatts Signal powerenergy determines its resistance to noise

dttgdttgEg )(|)(| 2

T

T

T

T

T

T dttgT

dttgT

P 22 )(2

1lim|)(|

2

1lim

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 12: Vidyalankar final-essentials of communication systems

Signal Energy and Power The energy in a signal g(t) is

The power in a signal g(t) is

Power is often expression in dBw or dBm [10 log10 P] dBW is dB power relative to Watts [10 log10 (P001)] dBm is dB power relative to mWatts Signal powerenergy determines its resistance to noise

dttgdttgEg )(|)(| 2

T

T

T

T

T

T dttgT

dttgT

P 22 )(2

1lim|)(|

2

1lim

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 13: Vidyalankar final-essentials of communication systems

The Communication System

Communication systems modulate analog signals or bits for transmission over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 14: Vidyalankar final-essentials of communication systems

The Backdrop Data rates over channels with noise have a fundamental capacity limit

Signal energy and power determine resistance to noise

Communication system shift scale and invert signals

Unit impulse and step functions important for analysis

Fourier series represents periodic signals in terms of exponential or sinusoidal basis functions

Exponentials are eigenfunctions of LTI filters

Fourier transform is the spectral components of a signal

Rectangle in time is sinc in frequency Time-limited signals are not bandlimited and vice versa

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 15: Vidyalankar final-essentials of communication systems

SourceEncoder

Communication System Block Diagram

SourceDecoderChannel ReceiverTransmitter

TextImagesVideo

)(tx )(ˆ tx)(ˆˆˆ

21

tmbb

)(21

tmbb

Source encoder converts message into message signal or bits

Transmitter converts message signal or bits into format appropriate for channel transmission (analogdigital signal)

Channel introduces distortion noise and interference

Receiver decodes received signal back to message signal

Source decoder decodes message signal back into original message

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 16: Vidyalankar final-essentials of communication systems

Analysis Outline

Channel Distortion and Equalization Ideal Filters Energy Spectral Density and its Properties Power Spectral Density and its Properties Filtering and Modulation based on PSD

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 17: Vidyalankar final-essentials of communication systems

Channel Distortion

Channels introduce linear distortion Electronic components introduce nonlinear

distortion

Simple equalizers invert channel distortion Can enhance noise power

X(f) X(f)+N(f)H(f)H(f) 1H(f)

N(f)

+

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 18: Vidyalankar final-essentials of communication systems

Filters

Low Pass Filter (linear phase)

Band Pass Filter (linear phase)

Most filtering (and other signal processing) is done digitally (AD followed by DSP)

1

-B B

11

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 19: Vidyalankar final-essentials of communication systems

Energy Spectral Density (ESD)

Signal energy

ESD measures signal energy per unit Hz

ESD of a modulation signal

dffGdttgEg22 |)(||)(|

fdffdttgE xg )(|)(| 2

Contains less information than Fourier Transform (no phase)

g(f) 25[g(f-f0)+ g(f+f0)]X

cos(2f0t)

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 20: Vidyalankar final-essentials of communication systems

Autocorrelation

Defined for real signals as g(t)=g(t)g(-t)Measures signal self-similarity at tCan be used for synchronization

ESD and autocorrelation FT pairs g(t) g(f)

Filtering based on ESD

)()()()()()()()()(2 ffGfGfGggdttgtg xg

g(f) |H(f)|2g (f)H(f)

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 21: Vidyalankar final-essentials of communication systems

Power Spectral Density

Similar to ESD but for power signals (P=Et) Distribution of signal power over frequency

2)(

2

1lim)( fG

TfS T

Tg

T

T

T dttgT

P 2|)(|2

1lim

|GT(f)|21

2T

gT(t)

-T T

T=Sg(f)

dffSdttgT

P g

T

T

Tg )(|)(|2

1lim 2

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 22: Vidyalankar final-essentials of communication systems

Filtering and Modulation

Filtering

ModulationWhen Sg(f) has bandwidth Bltf0

Sg(f) |H(f)|2Sg(f)H(f)

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)otherwise

+cross terms

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 23: Vidyalankar final-essentials of communication systems

Modulation and Autocorrelation

Modulation When Sg(f) has bandwidth Bltf0

Autocorrelation

Sg(f) 25[Sg(f-f0)+ Sg(f+f0)]X

cos(2fct)

)()(1

lim)()(2

1lim)(

22

2

fSfGT

dttgtgT

R gTT

T

TT

g

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 24: Vidyalankar final-essentials of communication systems

Probability Theory Mathematically characterizes random

events

Defined on a probability space (SAiP(bull)) Sample space of possible outcomes zi

Sample space has a subset of events Ai

Probability defined for these subsets

SA2

A3

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 25: Vidyalankar final-essentials of communication systems

Probability Measures-I

P(S)=1 0P(A)1 for all events A If (AB)= then P(AUB)=P(A)+P(B)

Conditional Probability P(B|A)=P(A B)P(A) Bayes Rule P(B|A)=P(A|B)P(B)P(A)

Independent Events A and B are independent if P(A B)=P(B)P(A) Independence is a property of P(bull) For independent events P(B|A)=P(B)

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 26: Vidyalankar final-essentials of communication systems

Probability Measure-II

Bernoulli Trials Total Probability Theorem

Let A1A2 hellip An be disjoint with iAi=S Then

Random Variables and their CDF and pdf CDF Fx(x)=P(xx)

pdf px(x)=dFx(x)dx

Means Moments and Variance

knk ppk

ntrialsninsuccesseskp

)1()(

A1A2 A3

S

B

P1

P3

P2

0 1 2 3

x

x

x

S

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 27: Vidyalankar final-essentials of communication systems

Gaussian Random Variables

pdf defined in terms of mean and variance

Gaussian CDF defined by Q function

])[( 22

2

1)(

x

X exp

x

x

N(2) Z~N()Tails decreaseexponentially

dxeyQy

x

22

2

1)(

2erfc5)(1)()( xxQx

QxFxXp X

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 28: Vidyalankar final-essentials of communication systems

Several Random Variables

Let X and Y be defined on (SAiP(bull))

Joint CDF FX Y(x y)=P (x x y y)

Joint pdf

Conditional densities

Independent RVs

ddpyxFyxpy x

)()()( xyxyxy

)()()x|( xxyy xpyxpxyp

)()()( yxxy ypxpyxp

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 29: Vidyalankar final-essentials of communication systems

Sums of Random Variables and the Central Limit Theorem Sums of RVs z=x + y

Pz (z)=py (y) px (x) Mean of sum is sum of means Variance of sum is sum of variances

Central Limit Theorem x1hellipxn iid Let y=ixi z=(y-E[y])sY

As n z becomes Gaussian E[y]=0 sy2=1

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 30: Vidyalankar final-essentials of communication systems

Stationarity Mean Autocorrelation

A random process is (strictly) stationary if time shifts donrsquot change probability P(x(t1)x1x(t2) x2hellipx(tn) xn)=

P(x(t1+T)x1x(t2+T) x2hellipx(tn+T) xn)

True for all T and all sets of sample times Mean of random process E[x(t)]=

Stationary process E[X(t)]= Autocorrelation of a random process

Defined as RX(t1t2)= E[x(t1)x(t2)]] Stationary process Rx(t1t2)=RX(t2-t1) Correlation of process samples over time

x(t)

x

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 31: Vidyalankar final-essentials of communication systems

Wide Sense Stationary (WSS) A process is WSS if

E[x(t)] is constant

RX(t1t2)= E[X(t1)X(t2)]]=RX(t2-t1)= RX (t) Intuitively stationary in 1st and 2nd moments

Ergodic WSS processes Have the property that time averages equal

probabilistic averages Allow probability characteristics to be obtained

from a single sample over time

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 32: Vidyalankar final-essentials of communication systems

Power Spectral Density (PSD)

Defined only for WSS processes FT of autocorrelation function RX (t) SX (f) E[X2(t)]= SX (f) df White Noise Flat PSD

Good approximation in practice

Modulation

5N0() 5N0

Sn(f)Rn()

f

Sn(f) 25[Sn(f-fc)+ Sn(f-fc)]X

cos(2fct+)

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 33: Vidyalankar final-essentials of communication systems

Gaussian Processes

z(t) is a Gaussian process if its samples are jointly Gaussian

Filtering a Gaussian process results in a Gaussian process

Integrating a Gaussian process results in a Gaussian random variable

T

g dttxtgY0

)()(

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 34: Vidyalankar final-essentials of communication systems

Examples of noise in Communication Systems Gaussian processes

Filtering a Gaussian process yields a Gaussian process

Sampling a Gaussian process yields jointly Gaussian RVs

If the autocorrelation at the sample times is zero the RVs are independent

The signal-to-noise power ratio (SNR) is obtained by integrating the PSD of the signal and integrating the PSD of the noise

In digital communications the bit value is obtained by integrating the signal and the probability of error by integrating Gaussian noise

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 35: Vidyalankar final-essentials of communication systems

Introduction to Carrier Modulation

Basic concept is to vary carrier signal relative to information signal or bitsThe carrier frequency is allocated by a

regulatory body like the FCC ndash spectrum is pretty crowded at this point

Analog modulation varies amplitude (AM) frequency (FM) or phase (PM) of carrier

Digital modulation varies amplitude (MAM) phase (PSK) pulse (PAM) or amplitudephase (QAM)

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 36: Vidyalankar final-essentials of communication systems

Double Sideband (Suppressed Carrier) Amplitude Modulation

Modulated signal is s (t)=m(t)cos(2pi fct) Called double-sideband suppressed carrier

(DSBSC) AM

Generation of DSB-SC AM modulation Direct multiplication (impractical) Nonlinear modulators Basic premise is to add

m(t) and the carrier then perform a nonlinear operation

Generates desired signal s(t) plus extra terms that are filtered out

Examples include diodetransistor modulators switch modulators and ring modulators

)]()([5)2cos()()( ccc ffSffStftmts

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 37: Vidyalankar final-essentials of communication systems

Coherent Detection of DSBAM

Detector uses another DSB-SC AM modulator

Demodulated signal macute(t)=5cos(f2-f1)m(t) Phase offset if f2-f1=p2 macute(t)=0

Coherent detection via PLL (f2f1) required Will study at end of AM discussion

m(t)

cos(ct+

DSBSCModulator

s(t) DSBSCModulator LPF

macute(t)

cos(ct+

Channel

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 38: Vidyalankar final-essentials of communication systems

Introduction to Angle Modulation and FM

Information encoded in carrier freqphase Modulated signal is s(t)=Accos(q(t))

q (t)=f (m (t))

Standard FM q (t)=2pfct+2pkfm(t)dt Instantaneous frequency fi=fc + kf m(t) Signal robust to amplitude variations Robust to signal reflections and refractions

Analysis is nonlinear Hard to analyze

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 39: Vidyalankar final-essentials of communication systems

FM Bandwidth and Carsonrsquos Rule

Frequency Deviation Df=kf max |m (t)| Maximum deviation of wi from wc wi =wc + kf m(t)

Carsonrsquos Rule

Bs depends on maximum deviation from wc AND how fast wi changes

Narrowband FM DfltltBmBs2Bm Wideband FM DfgtgtBm Bs2Df

Bs2f+2Bm

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 40: Vidyalankar final-essentials of communication systems

Spectral Analysis of FM

S (t)= A cos (wc t + kf m (a) da)Very hard to analyze for general m(t)

Let m(t)=cos (wm t) Bandwidth fm

S(f) sequence of d functions at f=fc plusmn nfm

If Df ltltfm Bessel function small for f(fcfm)

If Df gtgtfm significant components up to fcplusmnDf

fcfc+fmfc+2

fm

fc+3fm

fc+ 4fm

fc -4fmfc -3fm

fc -2fm

fc-fm

f

helliphellip5AcJn()

B2f WBFM

5AcJn()

S(f) for m(t)=cos(2fmt)

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 41: Vidyalankar final-essentials of communication systems

Generating FM Signals

NBFM

WBFM Direct Method Modulate a VCO with m(t)

Indirect Method

m(t) ProductModulator

Asin(ct)

s(t)2kf(middot)dt

(t)

-90o LO

+

Accos(ct)+

-

)()()())(22cos()( 1120111 tsatsatsdmktfAts nn

t

c

termsother ))(22cos(011

tdmnktnfA

termsother ))(22(cos)(0112

tnncn dmktfAats

ProductModulator

(k1f1)

m(t) s1(t) NonlinearDevice

s2(t)BPF s(t)

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 42: Vidyalankar final-essentials of communication systems

FM Detection

Differentiator and Envelope Detector

Zero Crossing Detector Uses rate of zero crossings to estimate wi

Phase Lock Loop (PLL) Uses VCO and feedback to extract m(t)

t

fcfc dmkttmkAts ])(sin[)]([)(

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 43: Vidyalankar final-essentials of communication systems

Introduction to Digital Modulation Most information today is in bits Baseband digital modulation converts bits into analog signals y(t)

(bits encoded in amplitude)

Bandwidth and PSD of y(t) determined by pulse shape p(t) and ak

If pulse duration is bit time Tb modulation called non-return to zero (NRZ) if less than Tb called return to zero (RZ)

)()()()()()( bk

kbk

k kTtatxfortptxkTtpaty

AawithpolarforTfPAfSfPfS kbxy |)(|)(|)(|)( 222

1 0 1 1 0 1 0 1 1 0On-Off Polar

t tTb

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 44: Vidyalankar final-essentials of communication systems

Pulse Shaping

Pulse shaping is the design of pulse p(t) Want pulses that have zero value at sample times nT

Rectangular pulses donrsquot have good BW properties

Nyquist pulses allow tradeoff of bandwidth characteristics and sensitivity to timing errors

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 45: Vidyalankar final-essentials of communication systems

Passband Digital Modulation

Changes amplitude (ASK) phase (PSK) or frequency (FSK) of carrier relative to bits

We use BB digital modulation as the information signal m(t) to encode bits ie m(t) is on-off etc

Passband digital modulation for ASKPSK) is a special case of DSBSC has form

FSK is a special case of FM

)cos()()(

ttmts ck

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 46: Vidyalankar final-essentials of communication systems

ASK PSK and FSK

Amplitude Shift Keying (ASK)

Phase Shift Keying (PSK)

Frequency Shift Keying

)0(0)(0

)1()()cos()cos()()(

b

bcc nTb

AnTmtAttmts

1 0 1 1

1 0 1 1

1 0 1 1

AM Modulation

AM Modulation

FM Modulation

m(t)

m(t)

)0()()cos(

)1()()cos()cos()()(

AnTmtA

AnTmtAttmts

bc

bcc

AnTmtA

AnTmtAts

b

b

)()cos(

)()cos()(

0

1

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 47: Vidyalankar final-essentials of communication systems

ASKPSK Demodulation

Similar to AM demodulation but only need to choose between one of two values (need coherent detection)

Decision device determines which of R0 or R1 that R(nTb) is closest to Noise immunity DN is half the distance between R0 and R1

Bit errors occur when noise exceeds this immunity

s(t)

cos(ct+)

bT

dt0

)(

nTb

Decision Device

ldquo1rdquo or ldquo0rdquo r(nTb)

R0

R1

a

r(nTb)

r(nTb)+

Integrator (LPF)

N

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 48: Vidyalankar final-essentials of communication systems

Noise in ASKPSK

Probability of bit error Pb=p (|N ( nTb)|gtDN=5|R1-R0|)

N ( n Tb) is a Gaussian RV N ~ N( m=0s2=25NoTb) For x~N(01) Define Q (z)=p (xgtz)

ASK

PSK

0

)225( NE

bbbbQTENpP

0

2)25( NE

bbbbQTENpP

s(t)

cos(ct)

bT

0

nTb

R(nTb)+N(nTb) ldquo1rdquo or ldquo0rdquo +

N(t)

ChannelN

R1

R0

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 49: Vidyalankar final-essentials of communication systems

FSK Demodulation

Minimum frequency separation required to differentiate |f1-f2|5nTb (MSK uses minimum separation of n=1) With this separation R1=0 if ldquo0rdquo sent R0=0 if ldquo1rdquo sent

Comparator R1=5ATb if ldquo1rsquo sent R0=5ATb if ldquo0rdquo sent Comparator outputs ldquo1rdquo if (R1+N1)-(R2+N2)gt0 otherwise ldquo0rdquo

Error probability depends on N1-N2

s(t)

cos(21t)

bT

0

R1(nTb)+N1

ldquo1rdquo or ldquo0rdquo

cos(0t)

bT

0

nTb

R0(nTb)+N2

Comparator

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 50: Vidyalankar final-essentials of communication systems

FSK Error Probability

Analysis similar to ASKPSK

Pb=p(N1-N2gt5ATb)

Distribution of N1-N2 Sum of indep Gaussians is Gaussian (|f1-f2|5nTb ) Mean is sum of means Variance is sum of variances N1N2~N(m=0s2=25NoTb) (Same as in ASKPSK) N1-N2 ~ N(m=0s2=5NoTb)

Pb=p(N1-N2gt5ATb)= Q(5ATb5N0Tb) =Q(5TbA2N0)=Q(EbN0)

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 51: Vidyalankar final-essentials of communication systems

Summary of Digital Modulation

Pulse shaping used in both baseband and passband modulation to determine signal BW and resistance to impairments

Digital passband modulation encodes binary bits into the amplitude phase or frequency of the carrier

ASKPSK special case of AM FSK special case of FM

Noise immunity in receiver dictates how much noise reqd to make an error

White Gaussian noise process causes a Gaussian noise term to be added to the decision device input

Bit error probability with white noise is a function of the symbol energy to noise spectral density ratio

BPSK has lower error probability than ASK for same energy per bit

FSK same error prob as ASK less susceptible to amplitude fluctuations

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 52: Vidyalankar final-essentials of communication systems

Performance Degradation

Phase offset Dq reduces noise immunity by cos (Dq)

If noise is not mean zero causes Pb to increase in one direction

With timing offset integrate over [Dt Tb+Dt] Interference from subsequent bit

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 53: Vidyalankar final-essentials of communication systems

Multilevel Modulation

m bits encoded in pulse of duration Ts (Rb=mTs)

n constant over a symbol time Ts and can take M=2m different values on each pulse

Phase Shift Keying (MPSK)

Similar ideas in MFSK Demodulation similar to binary case

))(cos()( ttAts ncn

Higher data ratemore susceptible to noise

11

10

01

00

)23cos(

)cos(

)2cos(

)cos(

)(

tA

tA

tA

tA

ts

cc

cc

cc

cc

00 10 01 11

Ts

00 10 01 11

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 54: Vidyalankar final-essentials of communication systems

Key Points To Remember PSD and pulse shaping in BB modulation

PSD depends on pulse shape Nyquist pulses avoid ISI p ( n Tb)=0 Raised Cosine pulses trade BW efficiency for timing error

robustness Passband digital modulation for ASKPSK is a special case of

DSBSC

FSK is a special case of FM Demodulation uses a decision device to determine if a ldquo1rsquorsquo

or ldquo0rsquorsquo was sent Noise can cause the decision device to output an erroneous

bit

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 55: Vidyalankar final-essentials of communication systems

The Interpretations Communication systems modulate analog signals or bits for transmission

over channel

The building blocks of a communication system convert information into an electronic format for transmission then convert it back to its original format after reception

Goal of transmitter (modulator) and receiver (demodulator) is to mitigate distortionnoise from the channel

Digital systems are more robust to noise and interference

Performance metric for analog systems is fidelity for digital it is rate and error probability

Data rates over channels with noise have a fundamental capacity limit

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 56: Vidyalankar final-essentials of communication systems

What is Telemetry

Telemetry The process of measuring at a distance

Aeronautical telemetry The process of making measurements on an aeronautical vehicle and sending those measurements to a distant location for analysis

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 57: Vidyalankar final-essentials of communication systems

TELEMETERING APPLICATIONS

The use of telemetry spectrum is common to many different nations and many purposes National defense Commercial aerospace industry Space applications Scientific research

The primary telemetering applications are Range and range support systems

Land mobile Sea ranges Air ranges

Space-based telemetry systems Meteorological telemetry

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 58: Vidyalankar final-essentials of communication systems

Telemetry Use in Precision Agriculture

1048729Differential GPS1048729Mobile phone reporting and control of center pivot irrigation systems1048729Soil moisture sensor networks1048729Climate control for high value crops1048729Real-time monitoring of equipment and people

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 59: Vidyalankar final-essentials of communication systems

Current Band-Allocations

Band (MHz)ITU All

Regions USCommon Europe UK France Italy

Other European Austria Finland

Norway Spain Sweden Australia Canada

4400-4800 X GX - harmonized

military bandG G X Defense All X Defense

G 4460-4540

4800-49404800-4825 4835-4940

G G G Finland SpainG 4900-4940

4940-4990 4940-4950 G G Finland Spain

5850-5925 X X G X DefenseAustria Norway Spain Sweden

X

6875-7125 X NG NG Spain Sweden X

7125-7300 X7145-7235 7250-

7300NG to 7250

Norway Spain Sweden

7125-7250

7900-8025 X

X - harmonized military band - 7900-7975 MHz

in NATO Countries

Austria(7942-8000) Norway Spain Sweden

14500-15300

X147145-151365

X - harmonized military band

14620-15230

G 14500-15250

14620-15350

Austria Norway Spain Sweden

147145-151365

Defense rest open

(secondary)

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 60: Vidyalankar final-essentials of communication systems

Spectrum Encroachments

239

0

235

0

220

0

225

0

230

0

2200-2290 MHz Unmanned 2360-2390 MHz Manned

1435-1525 MHz Manned Vehicle (L Band) Telemetry

2200-2390 MHz Manned and Unmanned Vehicle (S Band) Telemetry

152

5

150

0

143

5

146

0

148

5

One AC can easily use over 20MHz of spectrum

for a single mission

WARC 92

BBA 97

Terrestrial DAB (Canada) CARIBSS MediaStar

WARC 92US Alternative

Thank You

Page 61: Vidyalankar final-essentials of communication systems

Thank You