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Transcript of UEE3504: Introduction to Communication Systems Po-Ning Chen, Professor Dept. of Electrical and...
UEE3504: Introduction to Communication Systems
Po-Ning Chen, Professor
Dept. of Electrical and Computer Eng.
National Chiao Tung University
Background and Preview
To give you a basic understanding of communications
© Po-Ning [email protected] Background 3
Figure-1 Theory
The next figure is always the “Figure 1” in every book regarding communications.
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Communications
What is communication (or more specifically, communication engineering)? The transmission of information from one point to
another through a succession of certain processes.
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Basic Elements Regard Communications
Source of information Voice, music, picture, or computer data
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Basic Elements Regard Communications
Transmitter Source → Source Symbol (i.e., Source Word)
Symbolize the information from a source Source Symbol → Code Word
Encode the source symbol so that the other sources (i.e., noise and interfering signal) can hardly interfere the information transmission.
Code Word → Channel Symbol (i.e., Transmitted Signals) Modulate the code word into a form that is suitable for
transmission over the channel, which involves varying some parameter of a carrier wave in accordance with the message signal.
© Po-Ning [email protected] Background 7
Basic Elements Regard Communications
Noise/Interference Unwanted waves that tend to disturb the
transmission and processing of messages. Could be internal or external to the system. Could be additive or multiplicative (or both) to the
information-bearing signals.
© Po-Ning [email protected] Background 8
Basic Elements Regard Communications
Receiver Hard Decision
Channel Symbol → Code Bit Decode from Code Bits to Code Word Code Word → Source Symbol → Source
Soft Decision Decode from Channel Symbol to Code Word Code Word → Source Symbol → Source
© Po-Ning [email protected] Background 9
Example: Basic Elements Regard Communications
Source = An alphabet “A”
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Example : Basic Elements Regard Communications
Transmitter Source “A” → Binary Source Symbol (01000001)
Symbolize the information from a source
Source Symbol (01000001) → Code Word (000 111 000 000 000 000 000 111) Encode the source symbol by the three-times repetition code
so that the other sources (i.e., noise and interfering signals) can hardly interfere the information transmission.
001, 010, 011, 100, 101, 110 are not code words. Hence, their appearance is possible only when noise is introduced.
© Po-Ning [email protected] Background 11
Example : Basic Elements Regard Communications
Code Word (000 111 000 000 000 000 000 111) → Channel Symbol (000 555 000 000 000 000 000 555 ) Modulate the code word into some channel-permissible
(physical-medium permissible) symbols.
Due to Channel Interference, we receive: 010 442 222 033 011 020 032 434
© Po-Ning [email protected] Background 12
Example : Basic Elements Regard Communications
Receiver Hard Decision
Channel Symbol 010 442 222 033 011 020 032 434 → Code Bit (Threshold 2.5) 000 110 000 011 000 000 010 111
Decode from Code Bits to Code Word (Majority Rule) 000 111 000 111 000 000 000 111
Code Word 000 111 000 111 000 000 000 111 → Source Symbol 01010001 → Source “Q”
© Po-Ning [email protected] Background 13
Example : Basic Elements Regard Communications
Receiver Soft Decision
Decode from Channel Symbol 010 442 222 033 011 020 032 434 to (channel-symbolized) Code Word 000 555 000 000 000 000 000 555 By finding the minimum distance to legitimate codewords
000 and 111. E.g., d(033, 000) = (00)2+(30)2+(30)2 = 18 d(033, 555) = (05)2+(35)2+(35)2 = 33
Code Word 000 111 000 000 000 000 000 111 → Source Symbol 01000001→ Source “A”
© Po-Ning [email protected] Background 14
Basic Modes of Communications
Broadcasting Often, uni-directional. A single powerful transmitter to numerous
(inexpensive) receivers Example. Radio and TV.
Point-to-point communication Often, bi-directional. Two entities exchange information. Example. Telephone.
© Po-Ning [email protected] Background 15
Feature of Communications
Statistics The source is statistical in nature. The noise and interference are naturally random. Principles of Communication Engineering:Principles of Communication Engineering: How to
design a communication system only based on the knowledge of the statistics of the source and interferences (without knowing exactly what the true source and interference are)?
© Po-Ning [email protected] Background 16
Feature of Communications
Example Source
We do not know if the next source symbol is 0 or 1. But, we do know the probability of the next source
symbol being 0, and also, the probability of the next source symbol being 1.
Noise/Interference We do not know what value the noise/interference will
take? But, we do know the noise is, say, Gaussian
distributed.
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Feature of Communications
This is the reason why “Probabilities” (Chapter 1) is considered an important background to communication study.
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Primary Communication Resources
Primary Communication Resources are something “known” at the design stage. As aforementioned, source and noise/interference
are (often) something “unknown” at the design stage.
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Primary Communication Resources Examples of Primary Communication
Resources Transmitted Power
Specifically, averaged power of the transmitted signals. A more useful measure than the absolute transmitted
power is the signal-to noise power ratio (SNR), defined as the ratio of the average signal power to the average noise power. This quantity is often expressed in dB, 10 log10(SNR).
Channel Bandwidth The band of frequencies for use of transmitting
messages.
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Primary Communication Resources
Design principle of a communication system How to efficiently use (usually in a tradeoff
fashion) the communication resources!
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Sources of Information
“Sources” can sometimes be viewed as one kind of Communication Resources. For example, there are systems designed
specifically for “exchanging voices.” Such a system may not be apt to transmit computer
data. This introduces the subjects of “Source-Specific
Communication.” Next, we brief several sources commonly seen in
the literature.
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Sources of Information: (1) Speech
Features Voice spectrum extends well beyond 10kHz. Most of the average power is concentrated in the
range of 100 to 600 Hz.
A band of 300 to 3100 Hz gives good articulation. The sound wave propagates through the air at a
speed of 300 meter/second.
Do Re Mi Fa So La Si Do
261.6 293.7 329.6 349.2 392.0 440 493.9 523Freq (Hz)
Pitch Name
Schematic representation of the vocal system
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Sources of Information: (1) Speech
The speech-production process may be viewed as a form of filtering: A sound source excites a vocal tract filter.
D
D
a1
a9
a10
+
Excitation Speech
+
+
+
LipsLips
Vocal TractVocal Tract
Glottal VolumeGlottal Volume
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Sources of Information: Speech
As the sound propagates along the vocal tract, the spectrum (i.e., frequency content) is shaped by the frequency selectivity of the vocal tract —a resonance phenomenon observed in organ pipe.
So the hearing mechanism is (and should be) sensitive to frequency.
© Po-Ning [email protected] Background 26
Source of Information: Music
Originate from musical instruments, such as piano, violin, and flute.
It consists of: Melody: A time sequence of sounds. Harmony: A set of simultaneous sounds.
Different from speech, the spectrum of a music source may extend up to about 15 KHz. Accordingly, a much wider bandwidth resource is
demanded.
© Po-Ning [email protected] Background 27
Source of Information: Pictures
Two dimensional information. Classifications
Dynamic pictures – Video, such as North American Audio TV (NAA-TV)
Still pictures – Facsimile. To transmit still picture over a telephone channel.
© Po-Ning [email protected] Background 28
Source of Information: NAA-TV
North American Analog TV 525 horizontal lines, decomposed into two 262.5
line interlaced fields (See the next slide.) Completion of each interlaced field takes 1/60
second Horizontal line-scanning frequency is 262.5/(1/60) =
15.75 KHz. Hence, 30 still pictures are shown per second. The human “persistence of vision” phenomenon
will perceive these still pictures to be moving pictures.
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Source of Information: NAA-TV
In the NTSC (National Television System Committee) system, a total of 4.2 MHz bandwidth is demanded for TV transmission.
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Source of Information: Computer Data
The first code developed specifically for computer communication (1967) – ASCII (American Standard Code for Information Interchange).
© Po-Ning [email protected] Background 32
Source of Information: Computer Data
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Source of Information: Computer Data
ASCII (American Standard Code for
Information Interchange) 7-bit code for alphabetic numerical characters Bit 8 is sometimes used as parity-check bit or used
to form the extended ASCII code Even parity: Total number of 1’s is even. Odd parity: Total number of 1’s is odd.
Extended ASCII code can be displayed but cannot necessarily be printed out.
Bit originates from “Binary Digit.”
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Source of Information: Computer Data
Since ASCII is defined for communication, it also includes some symbols for communication purpose such as ENQ (enquiry) – 05X ETB (end of transmission block) – 17X
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Source of Information: Computer Data
RS (Recommended Standard) -232 Transmission Synchronous Asynchronous
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Source of Information: Computer Data
Asynchronous Serial Data No clock or timing signal required. ST : start bit S : stop bit P : parity bit D6~D0 : data bits (often, exact one ASCII character) Usually, 10 bit frame with even-parity/7-data-bit or
no-parity/8-data-bit.
S ST D0 D1 D2 D3 D4 D5 D6 P S ST D0 D1 D2 D3 D4 D5 D6 P S
frame
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Source of Information: Computer Data
Synchronous Serial Data No start and stop bits required. P : parity bit D6~D0 : data bits (ASCII) Clock : Timing signal. Note that it requires sync character (after a certain
number of frames) to avoid losing synchronization. If two sync characters are used. it is called bi-sync.
D0 D1 D2 D3 D4 D5 D6 P D0 D1 D2 D3 D4Data
Clock
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Source of Information: Computer Data
Windows 98 Baud rate : 110 baud~921600
baud (The # is different for different computers)
(E)ven parity, (O)dd parity, (N)one-parity, Mark, Space
4~8 Data-bit 1, 1.5, 2 Stop-bit
The name of “mark” and “space” for 1 and 0 comes from the days of telegraphy.
© Po-Ning [email protected] Background 39
Source of Information: Computer Data
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Source of Information: Computer Data
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Source of Information: Computer Data
The computer data stream so formed is then applied to a device called a modem (modulator-demodulator).
Unlike source traffic from speech or video, the computer data is often bursty rather than continuous.
© Po-Ning [email protected] Background 42
Missed Part of Figure-1 in Textbook
Source before entering the transmitter is often compressed (in order to save time or space).
This part is missed in Figure 1 of the textbook.
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With a source encoder, a digital communication system (rather an analog communication system) is formed.
© Po-Ning [email protected] Background 44
Data Compression
Lossless Data Compression (or Data Compaction) Completely reversible (or asymptotically
reversible). E.g., Lempel-Ziv algorithm (PKZIP, compress,
etc), which will be introduced in Chapter 9. Lossy Data Compression
Non-reversible with loss of information in a controlled manner.
E.g., JPEG, MPEG, etc.
© Po-Ning [email protected] Background 45
Lossy Data Compression for Images
JPEG (Joint Photographic Experts Group) An image coding standard Pixels are grouped in 8-by-8 block. DCT (discrete cosine transform) is then applied to
each block. Quantize each of the 64 DCT coefficients according
to a pre-specified table. Huffman-encode (introduced in Chapter 9) the
quantization results.
© Po-Ning [email protected] Background 46
Lossy Data Compression for Images
DCT
7
0
7
0
7
0
7
0
16
)12(cos
16
)12(cos),()()(
4
1),(
16
)12(cos
16
)12(cos),()()(
4
1),(
u v
x y
vyuxvuFvCuCyxf
vyuxyxfvCuCvuF
where
otherwise1
0for ,2
1)(
uuC
© Po-Ning [email protected] Background 47
Lossy Data Compression for Video
MPEG-1 (Motion Photographic Experts Group) video coding standard A video coding standard primarily for 30 fps
(frames per second) video Result in a bit-stream rate of 1.5 megabits per
second
© Po-Ning [email protected] Background 48
Lossy Data Compression for Video
Design objective : To reduce four kinds of redundancies: Interframe (temporal) redundancy
Its reduction is achieved through the use of prediction to estimate each frame from its neighbors.
The resulting prediction error is transmitted for motion estimation and compensation.
Interpixel redundancy within a frame Psychovisual redundancy Entropic coding redundancy
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Lossy Data Compression for Video
As with JPEG, the last three redundancies are reduced through the combined use of DCT, quantization and lossless entropic coding.
© Po-Ning [email protected] Background 50
Lossy Data Compression for Audio
MPEG-1 audio coding standard A perceptual (waveform) coder, as contrary to a
vocoder The amplitude-time waveform of the decoded audio
signal closely approximates that of the original audio signal.
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Lossy Data Compression for Audio
Encoding process Time-Frequency Mapping (sub-band decomposition) Psychoacoustic modeling (operates according to the
psychoacoustic behavior of the human auditory system)
Quantization and coding Frame-packing (format the quantized audio samples
into a decodable bit stream)
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Lossy Data Compression for Audio
Why Psychoacoustic modeling? Human ears have a perceptual phenomenon known as
auditory masking. Specifically, the human ear does not perceive
quantization noise in a given frequency band if the average noise power lies below the masking threshold
The masking threshold varies with frequency across the band.
Hence, a perceptual weighting filter is applied to waveforms before quantization.
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OSI
OSI (Open System Interconnection) model; the acronym DLC in the middle of the figure stands for data link control.
© Po-Ning [email protected] Background 54
Communication Networks
OSI reference model was developed by ISO (International Organization for Standardization) in 1977.
Figure 1 only concerns PHY layer. Now we take a quick look of its relation with
higher layers, such as Network layers.
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Communication Networks
Routing mechanisms Circuit Switching
Uninterrupted, exclusively use of links E.g., Telephone.
Packet Switching Shared-on-demand links
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Communication Networks
Why OSI reference model? Each layer can perform its related subset of
primitive functions without knowing the implementation details of the next lower layer.
The adjacent layers communicate through well-defined interfaces, which defines the services offered by the lower layer to the upper layer.
© Po-Ning [email protected] Background 58
Communication Networks
The entities that comprise the corresponding layers on different systems are referred to as peer processes.
Two peer entities then communicate through a well-defined set of rules of procedures, named Protocol.
Again, this text/course primarily considers PHY layer.
© Po-Ning [email protected] Background 59
Internet
Internet – A special communication network, as contrary to an Intranet.
Features of Internet Applications are carried out independently of the
technology employed to construct the network. The network technology is capable of evolving
without affecting the applications.
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Internet
Architecture of Internet
Direct Data ExchangeDirect Data Exchange
Cross-Router Data ExchangeCross-Router Data Exchange
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Internet Protocol (IP)
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Internet Service
Internet Service is “Best Effort” in nature. As a consequence, no guarantees of timely
transmission, and even delivery.
© Po-Ning [email protected] Background 63
Communication Channels
Channels, where the noise/interference resides, can be roughly divided into two groups: Guided propagation channels
E.g., telephone channels, coaxial cables, and optical fibers
Free propagation channels E.g., broadcast channels, mobile radio channels, and
satellite channels
© Po-Ning [email protected] Background 64
Communication Channels: (i) Telephone Channel
Features of telephone channel A channel performs “voice → electrical signal →
sound” Band-limited channel
A speech signal (male or female) is essentially limited to a band from 300 to 3100 Hz.
© Po-Ning [email protected] Background 65
Communication Channels: (i) Telephone Channel
Measures used in characterizing channel Insertion loss = 10 log10 (P0/PL)
PL = power delivered to a load from a source via the channel
P0 = power delivered to the same source notnot via the channel
PL
P0
Channel
Channel
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Communication Channels: (i) Telephone Channel
Envelope delay The negative of the derivative of the phase response with
respect to the angular frequency = 2f. Example. Envelope delay = a for the next channel.
fajefH 2)( )(tg )( atg
)].(exp[|)(|)( fjfHfH The phase response of a channel filter H(f) is (f), where
© Po-Ning [email protected] Background 67
Communication Channels: (i) Telephone Channel
Insertion Loss Envelope Delay
© Po-Ning [email protected] Background 68
Communication Channels: (ii) Coaxial Cable
A coaxial cable offers a greater degree of immunity to EMI, and a much higher bandwidth than twisted pair telephone lines.
Example of its applications Local area network in an office environment. Cable television
© Po-Ning [email protected] Background 69
Communication Channels: (iii) Optical Fiber
Features Enormous potential bandwidth
The bandwidth is roughly equal to 10% of the carrier frequency (2 1014 Hz).
Notably, the transmission attainable limit (for additive white Gaussian noise with SNR=10dB) is around
secondper Gigabit 86.6918
secondper bit 1091886.6
)101(log)102(
)1(log
13
10/102
13
2
dB
SNRBC
© Po-Ning [email protected] Background 70
Communication Channels: (iii) Optical Fiber
Low transmission loss 0.1dB/km
Immunity to electromagnetic interference Small size and weight (thinner than human hair) Ruggedness and flexibility
Possibility of being bent or twisted without damage.
© Po-Ning [email protected] Background 71
Communication Channels: (iv) Wireless Broadcast Channels
Transmission Up-convert the modulated baseband information-
bearing signal to Radio Frequency (RF) passband signal
Transmit the RF passband signal via antenna Reception
Pick up the radiated waves by an antenna. Down-convert the received passband signal to
baseband signal (perhaps through an intermediate step called the intermediate frequency (IF) band).
© Po-Ning [email protected] Background 72
Communication Channels: (v) Mobile Radio Channels
The main difference between this channel and the previous channel is the consideration of mobility. Due to mobility, there is no “line-of-sight” path for
communication; rather, radio propagation takes place mainly by way
of scattering from the surfaces of the surrounding buildings and by diffraction over and around them.
This results in a multipath fading transmission.
© Po-Ning [email protected] Background 73
Communication Channels: (v) Mobile Radio Channels
Transmitter Receiver
),( 11
),( 22
),( 33
)(
)(
)(
)(
33
22
11
tn
ts
ts
ts
)(ts
Notably, j and j can also be functions of time.
© Po-Ning [email protected] Background 74
Communication Channels: (vi) Satellite Channels
Satellite communications The satellite is placed in geostationary orbit.
Geostationary orbit1. The satellite orbits the Earth in exactly 24 hours
(geosynchronous).
2. The satellite is placed in orbit directly above the equator on an eastward heading.
It acts as a powerful repeater in the sky. It often uses 6 GHz for the uplink and 4 GHz for
the downlink.
© Po-Ning [email protected] Background 75
Communication Channels: (vi) Satellite Channels
The 6/4-GHz band offers the following attributes:1. Relatively inexpensive microwave equipment.
2. Low attenuation due to rainfall Rainfall is a primary atmospheric cause of signal loss.
3. Insignificant sky background noise The sky background noise due to random noise emissions
from galactic, solar and terrestrial sources reaches its lowest level between 1 and 10 GHz.
© Po-Ning [email protected] Background 76
Communication Channels: (vi) Satellite Channels
A typical satellite in the 6/4-GHz band is assigned a 500 MHz bandwidth, which is divided among 12 transponders. Each transponder can carry at least one color television
signal, 1200 voice circuits, or digital data at a rate of 50 Mb/s.
© Po-Ning [email protected] Background 77
Classifications of Communication Channels (according to the natures or resources)
Linear or non-linear A wireless radio channel is linear whereas a satellite
channel is usually non-linear Time invariant or time varying
An optical fiber is time invariant, whereas a mobile radio channel is typically time varying.
Band limited or power limited A telephone channel is band limited, whereas an
optical fiber link and a satellite channel are both power limited.
© Po-Ning [email protected] Background 78
Classification of Modulation Process
Continuous-wave modulation A sinusoidal wave is used as the carrier. It can be further classified as:
Amplitude modulation (AM) : Amplitude of the carrier is varied in accordance with the message.
Frequency modulation (FM) : Frequency of the carrier is varied in accordance with the message.
Phase modulation (PM) : Phase of the carrier is varied in accordance with the message.
© Po-Ning [email protected] Background 79
Classification of Modulation Process
Pulse modulation The carrier consists of a sequence of rectangular
pulses. It can be sub-divided to:
Analog pulse modulation Digital pulse modulation
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Classification of Modulation Process
Analog pulse modulation Pulse-amplitude modulation (PAM), pulse-duration
modulation (PDM), pulse-position modulation (PPM) The amplitude, duration, position of the pulses varies
in accordance with the message signals.
Digital pulse modulation Pulse-code modulation (PCM)
© Po-Ning [email protected] Background 81
Example of PAM (Telephone System)
Sampling the voice according to some clocks.
© Po-Ning [email protected] Background 82
Example of PCM
Originate from PAM, but with the following modifications. Convert the (sampled) pulse into bits, e.g., 8 bits. All 8 bits of the input PCM signal are gated to the
output port in parallel. The gate can now be designed using “truth table”
which facilitates system integration or multiplexing.
© Po-Ning [email protected] Background 83
What is multiplexing?
To combine (several modulated) signals for their simultaneous (or concurrent) transmission. Frequency-division multiplexing (FDM) Time-division multiplexing (TDM) Code-division multiplexing (CDM) Wavelength-division multiplexing (WDM),
specifically for use of optical fibers. Some treats WDM as a special case of FDM, since c =
f .
© Po-Ning [email protected] Background 84
Shannon’s Information Capacity Theorem
The underlying limit for digital communications
© Po-Ning [email protected] Background 85
Transmission Rate = Source code bit per second (Information bit per second)
© Po-Ning [email protected] Background 86
Shannon’s Information Capacity Theorem
Reliable transmission rate (for pre-specified modulator, channel and demodulator). The rate for which a proper design of channel
encoder-decode pair can fulfill arbitrarily small error requirement.
Shannon finds the general formula for the largest reliable transmission rate, which he baptized as “(coding) channel capacity.”
© Po-Ning [email protected] Background 87
Shannon’s Information Capacity Theorem
For additive white Gaussian noise asdemodulator output = modulator input + Gaussian
the channel capacity is equal toC = B log2(1+SNR) bit/second, where B is the bandwidth.
It took 45 years (1948~1993) of research to reach this “capacity!”
© Po-Ning [email protected] Background 88
An Exemplified Ideal Digital Communication Problem – Phase Shift Keying
ChannelEncoder
…0110Modulator
…,m(t), m(t), m(t), m(t)
m(t)
T
Carrier waveAccos(2fct)
s(t)
w(t)
x(t)
Local carriercos(2fct)
T
dt0
correlator
yT>< 0
0110…
No IF here because this is an ideal system.
© Po-Ning [email protected] Background 89
An Exemplified Ideal Digital Communication Problem – Phase Shift Keying
Assume that the local carrier (at the receiver end) is exactly the same as the transmitter carrier.
Assume that the correlator is completely synchronized with the transmitter. So the integration inside correlator covers a
complete message signal m(t). In other words, it will not happen that the integration inside correlator covers 80% of the current m(t) but 20% of the previous m(t).
T
cc
T
c
T
ccc
T
c
Tc
c
T
c
T
cc
T
ccc
T
c
T
cT
dttftwTA
dttftwdttfATA
dttftwdttf
A
dttftwdttfA
dttftwtfA
dttftwts
dttftxy
0
00
00
00
2
0
0
0
)2cos()(2
1
)2cos()()4cos(2
1
2
1
)2cos()(2
)4cos(1
)2cos()()2(cos
)2cos()]()2cos([
)2cos()]()([
)2cos()(
© Po-Ning [email protected] Background 90
(By assuming that fc is a multiple of 1/T.)
© Po-Ning [email protected] Background 91
An Exemplified Ideal Digital Communication Problem – Phase Shift Keying
Some interesting issues to consider: What if the local carrier does not equal the
transmitter carrier.
What if fc is not a multiple of 1/T.
What if the receiver does not synchronize with the transmitter?
What is the BER of this system?
T
tcrccT dttftwtfAy0
)2cos()]()2cos([
© Po-Ning [email protected] Background 92
An Exemplified Ideal Digital Communication Problem – Phase Shift Keying
Is the correlator receiver optimal in the sense of BER?
Is the “sign-decision” optimal in the sense of BER? Is the above combination optimal in the sense of
BER? Is the BER robust for imperfect system, such as
timing and carrier mismatch? Is the rectangular m(t) a fine choice? Moreover, is
PSK a fine choice? If affirmative, in what sense? ….
© Po-Ning [email protected] Background 93
An Exemplified Ideal Digital Communication Problem – Phase Shift Keying
All these problems will be hopefully answered in this course (and subsequent courses).