Channel Modelling – ETIN10 Lecture no: 1 · 2017-01-23 · 2012-01-16 Fredrik Tufvesson - ETIN10...

Fredrik Tufvesson & Carl GustafsonDepartment of Electrical and Information Technology

Lund University, [email protected]

Channel Modelling – ETIN10Lecture no:

2012-01-16 Fredrik Tufvesson - ETIN10 1

1Introduction


Contents

• Course information

• Why channel modeling?

• Review of concepts


COURSE INFORMATION


Course web-site

• All course information is available at:

http://www.eit.lth.se/course/ETIN10

(or www.eit.lth.se, -Education, -Courses, -Channel mod.)

• Most important:– Continuously updated schedule– Lecture handouts (available before each lecture)– Any additional material


Course web-site

• http://www.eit.lth.se/course/ETIN10


Textbook

Andreas F. MolischWireless Communications, 2nd edISBN: 978-0-470-74186-3Wiley/IEEE pressThe second edition will be used!• Available, e.g., through:

– Lexis, www.lexis.se– Amazon U.K., www.amazon.co.uk– Wiley, eu.wiley.com– etc.

• Authored by Andreas F. Molisch, former professor of Radio Systems at Lund University/LTH.


Schedule

• Three recurring components– Lectures: Carl Gustafson

Mondays (8-10, 2311) and Thursdays (10-12, E:2311)– Exercise classes: Xuhong Li

Wednesdays (8-10), 4116 (Starting next week)• Two special components

– Assignments:Two assignments, where reports are handed in

– Written exam:– March 13, 14-19.00


Lectures

• Overview of the content in the textbook

• Additional material

• Application examples


Exercise classes

• A selection of suitable exercises is listed on the course web-site

• During exercise classes, some of the exercises will be analysed in detail

• By working through the exercises beforehand, it becomes easier to ask questions about the parts You find difficult.


Assignments

• There are two compulsory assingments.• Performed in groups of two students.• You will receive measured channel data in MATLAB-format,

– analysis– parameter extraction– conclusions

• Short reports are handed in within 7 days.• You are NOT allowed to share results or code between

groups!• THIS IS A COMPULSORY PART OF THE COURSE!• You need to submit the assignments in order to take the

written exam.


Why channel modeling?

• The performance of a radio system is ultimately determined by the radio channel!

• The channel model is the basis for – system design– algorithm design– antenna design etc.

• Knowledge about system and channel interaction is vital:– MIMO: multiple antenna systems– UWB: ultra wideband– Localization services– Beamforming techniques

Without reliable channel models, it is difficult to design radio systems that work well in real environments.


A rough breakdown into areas

Fundamental problemsin wireless communications

Propagationand antennas

Deterministic Probabilistic

Channel models

Narrow-bandchannels

Wide-bandchannels

Antennas

Digital transmissionover wireless channels

Modulation

Speech andchannel coding

Equalization

Diversity

Mobile communicationssystems

Multiple access

Cellular telephony

Wireless data networks

Speech coding


Noise

NNoise reference level

THE RADIO CHANNELA simple link budget

Transmitter Receiver

”POWER” [dB]

Transmitpower

TXP

Feederloss

TXfL ,

Antennagain

TXaG ,

Propagationloss

pL

Antennagain

RXaG ,

Feederloss

RXfL ,

C

Receivedpower

Gai

nLo

ss RequiredC/N at

receiverinput

CRITERIONTO MEET:

This is a simple version of the link budget.


THE RADIO CHANNELIt is more than just a loss• Some examples:

– behavior in time/space?– behavior in frequency?– directional properties?– bandwidth dependency?– behavior in delay?


A narrowband system described in complex notation (noise free)

( )exp 2 cj fπ ( ) ( )( )expt j tα θ ( )exp 2 cj fπ−

Transmitter ReceiverChannel

Attenuation Phase

( )x t ( )y t

( ) ( ) ( ) ( )( )( )expA t t j t tα φ θ= +

( ) ( ) ( )( )expx t A t j tφ=In:

( ) ( ) ( )( ) ( ) ( ) ( )( ) ( )exp exp 2 exp exp 2c cy t A t j t j f t t j t j f tφ π α θ π= −Out:

It is the behavior of the channel attenuation and phase weare going to model.


THE RADIO CHANNELSome properties

• Path loss– Roughly, received power decays exponentially with distance

• Large-scale fading– Large objects, compared to a wavelength, in the signal path

obstruct the signal

• Small-scale fading– Objects reflecting the signal causes multipath propagation

from transmitter to receiver -> constructive and destructive (self-)interference.

exponentn PropagatioDistance power dTransmitte power Received −×∝


THE RADIO CHANNELPath loss

Received power [log scale]

Distance, d [log scale]

TX RX

2/1 d∝

4/1 d∝


THE RADIO CHANNELPath loss

”POWER” [dB]

dBTXG |dBTXP |

dBRXG |

( )10

| 2

10

420log , free space

20log , ground planedB

TX RX

d

L dd

h h

πλ

⎧ ⎛ ⎞⎜ ⎟⎪⎝ ⎠⎪

= ⎨⎛ ⎞⎪⎜ ⎟⎪ ⎝ ⎠⎩

dBRXP |

|dBL

Two theoretical expressions forthe deterministic propagation loss asfunctions of distance:

There are other models, which wewill discuss later.


Large-scale fadingBasic principle

d

Received power

PositionA B C C

A

B

C

D


Large-scale fadingLog-normal distribution

Measurements confirm that in many situations, the large-scalefading of the received signal strength has a normal distributionin the dB domain.

”POWER” [dB]

dBTXP |

dBRXP |

|dBL

( ) ( )2| 0|| 2

||

1 exp22dB dB

dBF dBF dB

L Lpdf L

σπσ

⎛ ⎞−⎜ ⎟= −⎜ ⎟⎝ ⎠

Note dB scale

dBDeterministic meanvalue of path loss, L0|dB

( )|dBpdf L

Standard deviation: σF|dB is typically 3-10 dB.


Small-scale fadingTwo waves

Wave 1 + Wave 2

Wave 2

Wave 1

λAt least in this case, we can see that the interference patternchanges on the wavelength scale.


THE RADIO CHANNELSmall-scale fading (cont.)

RXTX

With a large number ofreflection points theinterference patternbecomes extremly

complicated.


Small-scale fadingMany incoming waves

1 1,r φ2 2,r φ

3 3,r φ4 4,r φ

,r φ

( ) ( ) ( ) ( ) ( )1 1 2 2 3 3 4 4exp exp exp exp expr j r j r j r j r jφ φ φ φ φ= + + +

1r1φ

2r 2φ

3r

3φ

4r4φ

r

φ

Many incoming waves withindependent amplitudes

and phases

Add them up as phasors


THE RADIO CHANNELSmall-scale fading (cont.)

Illustration of interference pattern from above

Transmitter

Reflector

Movement

Position

A B

A B

Received power [log scale]


Small-scale fadingRayleigh fading

No dominant component(no line-of-sight)

2D Gaussian(zero mean)

Tap distribution

( )2

2 2exp2

r rpdf rσ σ

⎛ ⎞= −⎜ ⎟

⎝ ⎠

Amplitude distribution

Rayleigh

0 1 2 30

0.2

0.4

0.6

0.8

r a=

No line-of-sightcomponent

TX RXX

( )Im a ( )Re a


Small-scale fadingDoppler shifts

c

rvθ

0f f ν= +

Frequency of received signal:

( )0 cosrvfc

ν θ= −

where the Doppler shift isReceiving antenna moves withspeed vr at an angle θ relativeto the propagation directionof the incoming wave, whichhas frequency f0.

The maximal Doppler shift is

max 0vfc

ν =


Small-scale fadingDoppler spectrum

Isotropic uncorrelatedscattering

RX

Uniform incomingpower distribution

(isotropic)

Uncorrelatedamplitudesand phases

Time correlaion

( ) ( ) ( ){ } ( )*0 max2t E a t a t t J tρ πνΔ = +Δ ∝ Δ

0 0.5 1 1.5 2-0.5

0

0.5

1

max tν Δ

RX movement

J0 is the Bessel function of the first kind.


Small-scale fadingRice fading

A dominant component(line of sight)

2D Gaussian(non-zero mean)

Tap distribution

A

Line-of-sight (LOS)component with

amplitude A.

( )2 2

02 2 2

2

2

exp2

Power in LOS componentPower in random components 2

r r A rApdf r I

Ak

σ σ σ

σ

⎛ ⎞+ ⎛ ⎞= −⎜ ⎟ ⎜ ⎟⎝ ⎠⎝ ⎠

= =

Amplitude distribution

Rice

r α=

0 1 2 30

0.5

1

1.5

2

2.5k = 30

k = 10

k = 0

TX RX

( )Im a ( )Re a

Channel Modelling – ETIN10 Lecture no: 1 · 2017-01-23 · 2012-01-16 Fredrik Tufvesson - ETIN10...

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Transcript of Channel Modelling – ETIN10 Lecture no: 1 · 2017-01-23 · 2012-01-16 Fredrik Tufvesson - ETIN10...