34
7. Channel Models

7. Channel Models

  • Upload
    carl

  • View
    66

  • Download
    1

Embed Size (px)

DESCRIPTION

7. Channel Models. 2. Medium Scale Fading : due to shadowing and obstacles. 3. Small Scale Fading : due to multipath. 1. Large Scale Fading : due to distance. Signal Losses due to three Effects:. Wireless Channel. - PowerPoint PPT Presentation

Citation preview

Page 1: 7.  Channel Models

7. Channel Models

Page 2: 7.  Channel Models

Signal Losses due to three Effects:

1. Large Scale Fading: due to

distance

2. Medium Scale Fading: due to shadowing and

obstacles 3. Small Scale Fading: due to

multipath

Page 3: 7.  Channel Models

Wireless Channel

Several Effects:• Path Loss due to dissipation of energy: it depends on distance only• Shadowing due to obstacles such as buildings, trees, walls. Is caused by

absorption, reflection, scattering …• Self-Interference due to Multipath.

transm

rec

PP

10log10

distancelog10

Frequencies of Interest: in the UHF (.3GHz – 3GHz) and SHF (3GHz – 30 GHz) bands;

Page 4: 7.  Channel Models

Path Loss due to Free Space Propagation:

Transmit antenna

Receive antenna

2

4rec transmP Pd

wavelength cF

d

Path Loss in dB:

10 10 1010log 20log ( ( )) 20log ( ( )) 32.45transm

rec

PL F MHz d kmP

1.1. Large Scale Fading: Free Space

For isotropic antennas:

Page 5: 7.  Channel Models

2. Medium Scale Fading: Losses due to Buildings, Trees, Hills, Walls …

pp LEL

The Power Loss in dB is random:

approximately gaussian with dB126

expected value

random, zero mean

Page 6: 7.  Channel Models

00

10log10}{ LddLE p

Path loss exponent

Reference distance• indoor 1-10m• outdoor 10-100m

Free space loss at reference distance

dB

Average Loss

10 0log ( / )d d

0pE L L

10110 010210

20dB

10 Values for Exponent :

Free Space 2Urban 2.7-3.5Indoors (LOS) 1.6-1.8Indoors(NLOS) 4-6

Page 7: 7.  Channel Models

• Okumura: urban macrocells 1-100km, frequencies 0.15-1.5GHz, BS antenna 30-100m high;

• Hata: similar to Okumura, but simplified• COST 231: Hata model extended by European study to 2GHz

Empirical Models for Propagation Losses to Environment

Page 8: 7.  Channel Models

3. Small Scale Fading due to Multipath.

a. Spreading in Time: different paths have different lengths;

time

Transmit Receive

0( ) ( )x t t t

0t

0( ) ( ) ...k ky t h t t

1 2 30t

2138

100 10 sec3 10c

Example for 100m path difference we have a time delay

Page 9: 7.  Channel Models

Typical values channel time spread:

channel

0( ) ( )x t t t

1 2 MAX0t

0t

1

Indoor 10 50 sec

Suburbs 2 10 2 secUrban 1 3 secHilly 3-10 sec

n

Page 10: 7.  Channel Models

b. Spreading in Frequency: motion causes frequency shift (Doppler)

time

time

Transmit Receive

Frequency (Hz)

Doppler Shift

v

cf

2( ) cj F tTx t X e

2( ) cj F F tRy t Y e

for each path

cF F

Page 11: 7.  Channel Models

time

Transmit Receive

v

Put everything together

time

)(tx )(ty

Page 12: 7.  Channel Models

Re{.}

tFj Ce 2 tFj Ce 2

)(th

)(tw

)(tgT

LPF

)(tgR

LPF

( )x t ( )y t

2 ( )( )( )( ) Re ( ) cj F tFy t x t ea t

Each path has … …shift in time …

…shift in frequency …

… attenuation…

(this causes small scale time variations)

paths

channel

Page 13: 7.  Channel Models

2.1 Statistical Models of Fading Channels

Several Reflectors:

Transmit

v

( )x t

t ( )y t

t

1

2

Page 14: 7.  Channel Models

For each path with NO Line Of Sight (NOLOS):

2 ( )( )( ) Re ( )c kj F tk

kk

Fy t a e x t

v( )y t average time delay

• each time delay

• each doppler shift

k

DF F

cos( )v t

t

Page 15: 7.  Channel Models

)2 ( )( 22( ) Re ( )c k cFF j F j F tj t

kkky t e e x t ea

2 ( )2( ) ( )c kj F Fj F tk

k

r t a e e x t

Assume: bandwidth of signal <<

( ) ( )kx t x t … leading to this:

Some mathematical manipulation …

k/1

2( ) Re ( ) cj F ty t r t e

( ) ( ) ( )r t c t x t

with 2 ( )2( ) c kj F Fj F t

kk

c t a e e random, time varying

Page 16: 7.  Channel Models

Statistical Model for the time varying coefficients

2 ( )2

1

( ) c kM

j F Fj F tk

k

c t a e e

randomBy the CLT is gaussian, zero mean, with:( )c t

*0( ) ( ) (2 )DE c t c t t P J F t

D Cv vF Fc

with the Doppler frequency shift.

Page 17: 7.  Channel Models

Each coefficient is complex, gaussian, WSS with autocorrelation

*0( ) ( ) (2 )DE c t c t t P J F t

( )c t

and PSD

20

2 1 if | |( ) (2 ) 1 ( / )

0 otherwise

DDD D

F FFS F FT J F t F F

with maximum Doppler frequency.DF

( )S F

DF F

This is called Jakes spectrum.

Page 18: 7.  Channel Models

Bottom Line. This:

time

v

time

)(tx )(ty

11( )c t

( )c t

N( )Nc t

( )y t)(tx

… can be modeled as:

delays

1

N

time time

time

Page 19: 7.  Channel Models

For each path

( ) ( )c t P c t

• unit power• time varying (from

autocorrelation)

• time invariant• from power distribution

Page 20: 7.  Channel Models

Parameters for a Multipath Channel (No Line of Sight):

Time delays: L 21 sec

Power Attenuations: LPPP 21 dB

Doppler Shift: DF Hz

)()()( txtcty

( ) ( )c t P c t

)(tc WSS with Jakes PSD

Summary of Channel Model:

Page 21: 7.  Channel Models

Non Line of Sight (NOLOS) and Line of Sight (LOS) Fading Channels1. Rayleigh (No Line of Sight). Specified by:

Time delays

Power distribution

],...,,[ 21 NT

],...,,[ 21 NPPPP

Maximum Doppler DF

0)}({ tcE

2. Ricean (Line of Sight) 0)}({ tcE

Same as Rayleigh, plus Ricean Factor

Power through LOS

Power through NOLOS

TotalLOS PK

KP

1

TotalNOLOS PK

P

1

1

K

Page 22: 7.  Channel Models

Simulink Example

-K-

TransmitterGain

B-FFT

SpectrumScope

RectangularQAM

Rectangular QAMModulatorBaseband

-K-

Receiver Gain

RayleighFading

Multipath RayleighFading Channel

-K-ChannelAttenuation

BernoulliBinary

Bernoulli BinaryGenerator

Rayleigh Fading Channel Parameters

M-QAM Modulation

Bit Rate

Page 23: 7.  Channel Models

Set Numerical Values:

modulation

power

channel

CD FcvF Recall the Doppler Frequency:

carrier freq.

sec/103 8 m

velocity

Easy to show that: GHzChkmHzD FvF /

Page 24: 7.  Channel Models

Channel Parameterization

1. Time Spread and Frequency Coherence Bandwidth2. Flat Fading vs Frequency Selective Fading3. Doppler Frequency Spread and Time Coherence4. Slow Fading vs Fast Fading

Page 25: 7.  Channel Models

1. Time Spread and Frequency Coherence Bandwidth

Try a number of experiments transmitting a narrow pulse at different random times

)()( ittptx

)(tp

We obtain a number of received pulses

( ) ( ) ( ) ( ) ( )i i i iy t c t p t t c t p t t

1tt 1 2

it t1 2

0

0

Nt t1 2 0

)( 11 itc2 2( )ic t

( )ic t

transmitted

Page 26: 7.  Channel Models

Take the average received power at time it t

1 2 0

1P2P P

2|)(| tcEP

MEAN

RMS

0

10

20

Received Power

time

More realistically:

Page 27: 7.  Channel Models

This defines the Coherence Bandwidth.Take a complex exponential signal with frequency . The response of the channel is:

)(2)()( MEANtFjetcty

If

)(tx F

1|| RMSF 2 ( )( ) ( ) MEANj F ty t c t e

then

i.e. the attenuation is not frequency dependent

Define the Frequency Coherence Bandwidth as

15c

RMS

B

Page 28: 7.  Channel Models

15c

RMS

B

frequencyCoherence Bandwidth

Channel “Flat” up to the Coherence Bandwidth

This means that the frequency response of the channel is “flat” within the coherence bandwidth:

Frequency CoherenceSignal Bandwidth <>

Frequency Selective Fading

Flat Fading Just attenuation, no distortion

Distortion!!!

Page 29: 7.  Channel Models

Example: Flat Fading

Channel : Delays T=[0 10e-6 15e-6] secPower P=[0, -3, -8] dBSymbol Rate Fs=10kHzDoppler Fd=0.1HzModulation QPSK

Spectrum: fairly uniform

Very low Inter Symbol Interference (ISI)

Page 30: 7.  Channel Models

Example: Frequency Selective Fading

Channel : Delays T=[0 10e-6 15e-6] secPower P=[0, -3, -8] dBSymbol Rate Fs=1MHzDoppler Fd=0.1HzModulation QPSK

Spectrum with deep variations

Very high ISI

Page 31: 7.  Channel Models

3. Doppler Frequency Spread and Time Coherence

Back to the experiment of sending pulses. Take autocorrelations:

)()()( * ttctcEtR

Where:

1tt 1 2

it t1 2

0

0

Nt t1 2 0

)( 11 itc2 2( )ic t

( )ic t

1( )R t2 ( )R t

( )R t

transmitted

Page 32: 7.  Channel Models

Take the FT of each one:

( )S F

DF F

This shows how the multipath characteristics change with time.It defines the Time Coherence:

)(tc

916C

D

TF

Within the Time Coherence the channel can be considered Time Invariant.

Page 33: 7.  Channel Models

Summary of Time/Frequency spread of the channel

Time Spread

Frequency Spread ),( FtS

F

t

RMS

DF

Frequency Coherence

15c

RMS

B

Time Coherence

916C

D

TF

mean

Page 34: 7.  Channel Models

Stanford University Interim (SUI) Channel Models

Extension of Work done at AT&T Wireless and Erceg etal.

Three terrain types:• Category A: Hilly/Moderate to Heavy Tree density;• Category B: Hilly/ Light Tree density or Flat/Moderate to Heavy Tree density• Category C: Flat/Light Tree density

Six different Scenarios (SUI-1 – SUI-6).Found in

IEEE 802.16.3c-01/29r4, “Channel Models for Wireless Applications,” http://wirelessman.org/tg3/contrib/802163c-01_29r4.pdfV. Erceg etal, “An Empirical Based Path Loss Model for Wireless Channels in Suburban Environments,” IEEE Selected Areas in Communications, Vol 17, no 7, July 1999