Simulation Model for Mobile Radio Channels

Simulation Model for Simulation Model for Mobile Radio Channels Mobile Radio Channels

Ciprian Romeo ComCiprian Romeo ComşaşaIolanda AlecsandrescuIolanda Alecsandrescu

Andrei MaiorescuAndrei MaiorescuIon BogdanIon Bogdan

[email protected]@etc.tuiasi.ro

Technical University “Gh. Asachi” IaTechnical University “Gh. Asachi” IaşşiiDepartment of TelecommunicationsDepartment of Telecommunications

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TecTechhnical Universitnical University “Gh. Asachi” Iay “Gh. Asachi” IaşşiiDepartment of TelecommunicationsDepartment of TelecommunicationsSlide Slide 22

Radio channelRadio channel

Diffraction

ReflectionScattering

Radio channel: propagation medium characterized by wave phenomena.

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FadingFading

Waves are received on different propagation ways => Multi-path Propagation.The propagation is realized mostly by reflection and diffraction.

The sum of waves received may have significant variations even on slow motion of receiver.This is called short-term fadingshort-term fading or fast fadingfast fading and follows a Rayleigh distribution.

LOS propagation

Diffraction

Reflection

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FadingFading

Waves are received on different propagation ways => Multi-path Propagation.The propagation is realized mostly by reflection and diffraction.

The sum of waves received may have significant variations even on slow motion of receiver.This is called short-term fadingshort-term fading or fast fadingfast fading and follows a Rayleigh distribution.

The mean of the received signal has slow variations on larger motion.This is called long-term fadinglong-term fading and follows a log-normal distribution.

Short-term fading

Long-term fading

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Channel ModelingChannel Modeling A channel model has to allow the evaluation of the propagation loses and theirs A channel model has to allow the evaluation of the propagation loses and theirs

variations (fading).variations (fading). The Suzuki model takes into account short-term fading with superimposed long-The Suzuki model takes into account short-term fading with superimposed long-

term log-normal variations of the mean of received signal:term log-normal variations of the mean of received signal:

( ) ( ) ( )t t t

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Analytical model – Stochastic Analytical model – Stochastic process: process:

( ) ( ) ( )t t t Extended Suzuki Stochastic process Log-normal process

models the short-time fadingmodels the short-time fading is obtained considering:is obtained considering:

complex zero mean Gaussian noise processcomplex zero mean Gaussian noise process

with cross-correlated quadrature components and with cross-correlated quadrature components and LOS component supposed to be independent of time (for short-time fading)LOS component supposed to be independent of time (for short-time fading)

is obtained as envelope of nonzero mean Gaussian noise processis obtained as envelope of nonzero mean Gaussian noise process

For particular values of environment parameters, this process For particular values of environment parameters, this process follows follows RiceRice, , RayleighRayleigh or or one-sided Gaussianone-sided Gaussian distribution. distribution.

1 2( ) ( ) ( )t t j t

2 ( )t1( )t

1 2

jm m j m e

( ) ( )t t m 2 21 1 2 2( ) ( ( ) ) ( ( ) )t t m t m

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Analytical model – Log-normal Analytical model – Log-normal process: process:

( ) ( ) ( )t t t Extended Suzuki Log-normal processStochastic process

models the long-time fading, caused by shadowing effectsmodels the long-time fading, caused by shadowing effects

is obtained from another real Gaussian noise process is obtained from another real Gaussian noise process with zero mean and unit variance:with zero mean and unit variance:

m and s are two environment parameters m and s are two environment parameters and are uncorrelatedand are uncorrelated( )t

3( )t

3( )t

3 ( )( ) m s tt e

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Simulation ModelSimulation Model

cross-correlatedcross-correlated Simulation coefficients:Simulation coefficients:

-Doppler coefficients-Doppler coefficients -discrete Doppler -discrete Doppler

frequenciesfrequencies - Doppler phases- Doppler phases

= number of = number of sinusoids used to sinusoids used to approximate the Gaussian approximate the Gaussian processesprocesses

1 2( ), ( )t t

,i nc

,i nf

,i n

1 2,N N

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SimulationSimulation A mixed signal simulation tool is used – Saber Designer with MAST languageA mixed signal simulation tool is used – Saber Designer with MAST language MAST = HDL => the channel model can be used for simulations deeper to MAST = HDL => the channel model can be used for simulations deeper to

hardware systemshardware systemsSimulation DataSimulation Data

Environment parameters:Environment parameters:

Number of sinusoids: NNumber of sinusoids: N11=25 and N=25 and N22=15.=15.

Number of samples NNumber of samples NSS=10=1088 and sampling period T and sampling period Taa=3=3·10·10-8-8s.s.

Maximum Doppler frequency fMaximum Doppler frequency fmaxmax=91Hz, corresponding to a vehicle’s speed of =91Hz, corresponding to a vehicle’s speed of

110Km/h.110Km/h.

Doppler coefficients cDoppler coefficients ci,ni,n and discrete Doppler frequencies f and discrete Doppler frequencies fi,ni,n are calculated at are calculated at

the beginning and kept constants during the simulation.the beginning and kept constants during the simulation. Doppler phases Doppler phases θθi,ni,n are modified at each simulation step given by sampling are modified at each simulation step given by sampling..

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Simulation results (1)Simulation results (1)

Envelope of the simulated extended Suzuki processEnvelope of the simulated extended Suzuki process

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Simulation results (2)Simulation results (2)

The differences between the generated signal distribution obtained as The differences between the generated signal distribution obtained as histogram and the analytical pdf are hardly observable.histogram and the analytical pdf are hardly observable.

The values for mean and standard deviation confirms this affirmationThe values for mean and standard deviation confirms this affirmation..

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ConclusionConclusion

Histogram of simulated extended Suzuki model, in cases of:Histogram of simulated extended Suzuki model, in cases of: Light shadowing Light shadowing log-normal distribution log-normal distribution Heavy shadowing Heavy shadowing Rice (or Rayleigh) distribution Rice (or Rayleigh) distribution

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Simulation Model for Mobile Radio Channels