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comm.RayleighChannel

Filter input signal through multipath Rayleigh fading channel

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Description

Thecomm.RayleighChannelSystem object™ filters an input signal through the multipath Rayleigh fading channel. For more information on fading model processing, see theMethodology for Simulating Multipath Fading Channelssection.

To filter an input signal through a multipath Rayleigh fading channel:

  1. Create thecomm.RayleighChannelobject and set its properties.

  2. Call the object with arguments, as if it were a function.

To learn more about how System objects work, seeWhat Are System Objects?

Creation

Syntax

rayleighchan = comm.RayleighChannel
rayleighchan = comm.RayleighChannel(Name,Value)

Description

rayleighchan= comm.RayleighChannelcreates a frequency-selective or frequency-flat multipath Rayleigh fading channel System object. This object filters a real or complex input signal through the multipath channel to obtain a channel-impaired signal.

example

rayleighchan= comm.RayleighChannel(Name,Value)sets properties using one or more name-value arguments. For example,'SampleRate',2sets the input signal sample rate to 2.

Properties

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Unless otherwise indicated, properties arenontunable, which means you cannot change their values after calling the object. Objects lock when you call them, and thereleasefunction unlocks them.

If a property istunable, you can change its value at any time.

For more information on changing property values, seeSystem Design in MATLAB Using System Objects.

Input signal sample rate in hertz, specified as a positive scalar.

Data Types:double

Discrete path delay in seconds, specified as a scalar or row vector.

  • When you setPathDelaysto a scalar, the channel is frequency flat.

  • When you setPathDelaysto a vector, the channel is frequency selective.

ThePathDelaysandAveragePathGainsproperties must be the same length.

Data Types:double

Average gains of the discrete paths in decibels, specified as a scalar or row vector. TheAveragePathGainsandPathDelaysproperties must be the same length.

Data Types:double

Normalize average path gains, specified as one of these logical values:

  • 1(true) — The fading processes are normalized so that the total power of the path gains, averaged over time, is 0 dB.

  • 0(false) — The total power of the path gains is not normalized.

TheAveragePathGainsproperty specifies the average powers of the path gains.

Data Types:logical

Maximum Doppler shift for all channel paths, specified as a nonnegative scalar. Units are in hertz.

多普勒频移的最大限制适用于每个channel path. When you set this property to0, the channel remains static for the entire input. You can use theresetobject function to generate a new channel realization. TheMaximumDopplerShiftproperty value must be smaller thanSampleRate/10/fcfor each path.fc我s the cutoff frequency factor of the path. For most Doppler spectrum types, the value offc我s 1. For Gaussian and bi-Gaussian Doppler spectrum types,fc我s dependent on the Doppler spectrum structure fields. For more details about howfc我s defined, see theCutoff Frequency Factorsection.

Data Types:double

Doppler spectrum shape for all channel paths, specified as a Doppler spectrum structure or a 1-by-NPcell array of Doppler spectrum structures. These Doppler spectrum structures must be outputs of the form returned from thedopplerfunction.NP我s the number of discrete delay paths specified by thePathDelaysproperty. TheMaximumDopplerShiftproperty defines the maximum Doppler shift value that theDopplerSpectrumproperty permits when you specify the Doppler spectrum..

  • When you setDopplerSpectrumto a single Doppler spectrum structure, all paths have the same specified Doppler spectrum.

  • When you setDopplerSpectrumto a cell array of Doppler spectrum structures, each path has the Doppler spectrum specified by the corresponding structure in the cell array.

Specify options for the spectrum type by using thespecType我nput to thedopplerfunction. If you set theFadingTechniqueproperty to'Sum of sinusoids', you must setDopplerSpectrumtodoppler('Jakes').

Dependencies

To enable this property, set theMaximumDopplerShiftproperty to a positive scalar.

Data Types:struct|cell

Channel filtering, specified as one of these logical values:

  • 1(true) — The channel accepts an input signal and produces a filtered output signal.

  • 0(false) — The object does not accept an input signal, produces no filtered output signal, and outputs only channel path gains. You must specify the duration of the fading process by using theNumSamplesproperty.

Data Types:logical

Output channel path gains, specified as a logical0(false) or1(true). Set this property totrueto output the channel path gains of the underlying fading process.

Dependencies

To enable this property, set theChannelFilteringproperty totrue.

Data Types:logical

Number of samples used for the duration of the fading process, specified as a nonnegative integer.

Tunable:Yes

Dependencies

To enable this property, set theChannelFilteringproperty tofalse.

Data Types:double

Path gain output data type, specified as'double'or'single'.

Dependencies

To enable this property, set theChannelFilteringproperty tofalse.

Data Types:查r|string

Channel model fading technique, specified as'Filtered Gaussian noise'or'Sum of sinusoids'.

Data Types:查r|string

Number of sinusoids used to model the fading process, specified as a positive integer.

Dependencies

To enable this property, set theFadingTechniqueproperty to'Sum of sinusoids'.

Data Types:double

Source to control the start time of the fading process, specified as'Property'or'Input port'.

  • When you setInitialTimeSourceto'Property', set the initial time offset by using theInitialTimeproperty.

  • When you setInitialTimeSourceto'Input port', specify the start time of the fading process by using the我nittime我nput argument. The input value can change in consecutive calls to the object.

Dependencies

To enable this property, set theFadingTechniqueproperty to'Sum of sinusoids'.

Data Types:查r|string

Initial time offset for the fading model in seconds, specified as a nonnegative scalar.

Whenmod(InitialTime/SampleRate)我s nonzero, the initial time offset is rounded up to the nearest sample position.

Dependencies

To enable this property, set theFadingTechniqueproperty to'Sum of sinusoids'and theInitialTimeSourceproperty to'Property'.

Data Types:double

Source of the random number stream, specified as'Global stream'or'mt19937ar with seed'.

  • When you specify'Global stream', the object uses the current global random number stream for random number generation. In this case, theresetobject function resets only the filters.

  • When you specify'mt19937ar with seed', the object uses the mt19937ar algorithm for random number generation. In this case, theresetobject function resets the filters and reinitializes the random number stream to the value of theSeedproperty.

Data Types:查r|string

Initial seed of the mt19937ar random number stream generator algorithm, specified as a nonnegative integer. When you call theresetobject function, it reinitializes the mt19937ar random number stream to theSeedvalue.

Dependencies

To enable this property, set theRandomStreamproperty to'mt19937ar with seed'.

Data Types:double

Channel visualization, specified as'Off','Impulse response','Frequency response','Impulse and frequency responses', or'Doppler spectrum'. For more information, see theChannel Visualizationtopic.

Dependencies

To enable this property, set theFadingTechniqueproperty to'Filtered Gaussian noise'.

Data Types:查r|string

Path used for displaying the Doppler spectrum, specified as a positive integer in the range [1,NP].NP我s the number of discrete delay paths specified by thePathDelaysproperty. Use this property to select the discrete path used in constructing a Doppler spectrum plot.

Dependencies

To enable this property, set theVisualizationproperty to'Doppler spectrum'.

Data Types:double

Percentage of samples to display, specified as'25%','10%','50%', or'100%'. Increasing the percentage improves display accuracy at the expense of simulation speed.

Dependencies

To enable this property, set theVisualizationproperty to'Impulse response','Frequency response', or'Impulse and frequency responses'.

Data Types:查r|string

Usage

Syntax

y = rayleighchan(x)
y = rayleighchan(x,inittime)
[y,pathgains] = rayleighchan(___)
pathgains = rayleighchan()
pathgains = rayleighchan(inittime)

Description

example

y= rayleighchan(x)filters the input signalxthrough a multipath Rayleigh fading channel and returns the result iny.

To enable this syntax, set theChannelFilteringproperty totrue.

example

y= rayleighchan(x,我nittime)specifies a start time for the fading process.

To enable this syntax, set theFadingTechniqueproperty to'Sum of sinusoids'and theInitialTimeSourceproperty to'Input port'.

example

[y,pathgains] = rayleighchan(___)also returns the channel path gains of the underlying multipath Rayleigh fading process inpathgainsusing any of the input argument combinations in the previous syntaxes.

To enable this syntax, set thePathGainsOutputPortproperty set totrue.

example

pathgains= rayleighchan()returns the channel path gains of the underlying fading process. In this case, the channel requires no input signal and acts as a source of path gains.

To enable this syntax, set theChannelFilteringproperty tofalse.

pathgains= rayleighchan(我nittime)returns the channel path gains of the underlying fading process beginning at the specified initial time. In this case, the channel requires no input signal and acts as a source of path gains.

To enable this syntax, set theFadingTechniqueproperty to'Sum of sinusoids', theInitialTimeSourceproperty to'Input port', and theChannelFilteringproperty tofalse.

Input Arguments

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Input signal, specified as anNS-by-1 vector, whereNS我s the number of samples.

Data Types:single|double
Complex Number Support:Yes

Initial time offset in seconds, specified as a nonnegative scalar.

Whenmod(我nittime/SampleRate)我s nonzero, the initial time offset is rounded up to the nearest sample position.

Data Types:single|double

Output Arguments

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Output signal, returned as anNS-by-1 vector of complex values with the same data precision as the input signalx.NS我s the number of samples.

Output path gains, returned as anNS-by-NPmatrix.NS我s the number of samples.NP我s the number of discrete delay paths specified by thePathDelaysproperty.pathgainscontains complex values.

When you set theChannelFilteringproperty tofalse, the data type of this output has the same precision as the input signalx. When you set theChannelFilteringproperty totrue, the data type of this output is specified by theOutputDataTypeproperty.

Object Functions

To use an object function, specify the System object as the first input argument. For example, to release system resources of a System object namedobj, use this syntax:

release(obj)

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我nfo Characteristic information about fading channel object
step RunSystem objectalgorithm
release Release resources and allow changes toSystem objectproperty values and input characteristics
reset Reset internal states ofSystem object

Examples

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Open Live Script

Produce the same multipath Rayleigh fading channel response by using two different methods for random number generation. The multipath Rayleigh fading channel System object includes two methods for random number generation. You can use the current global stream or the mt19937ar algorithm with a specified seed. By interacting with the global stream, the System object can produce the same outputs from these two methods.

Create a PSK modulator System object to modulate randomly generated data.

pskModulator = comm.PSKModulator; insig = randi([0,pskModulator.ModulationOrder-1],1024,1); channelInput = pskModulator(insig);

Create a multipath Rayleigh fading channel System object, specifying the random number generation method as the my19937ar algorithm and the random number seed as 22.

rayleighchan = comm.RayleighChannel(...'SampleRate',10e3,...'PathDelays',[0 1.5e-4],...'AveragePathGains',[2 3],...'NormalizePathGains',true,...'MaximumDopplerShift',30,...'DopplerSpectrum',{doppler('Gaussian',0.6),doppler('Flat')},...'RandomStream','mt19937ar with seed',...'Seed',22,...'PathGainsOutputPort',true);

Filter the modulated data by using the multipath Rayleigh fading channel System object.

[chanOut1,pathGains1] = rayleighchan(channelInput);

Set the System object to use the global stream for random number generation.

释放(rayleighchan);rayleighchan。RandomStream ='Global stream';

Set the global stream to have the same seed that you specified when creating the multipath Rayleigh fading channel System object.

rng(22)

Filter the modulated data by using the multipath Rayleigh fading channel System object again.

[chanOut2,pathGains2] = rayleighchan(channelInput);

Verify that the channel and path gain outputs are the same for each of the two methods.

我sequal(chanOut1,chanOut2)
ans =logical1
我sequal(pathGains1,pathGains2)
ans =logical1
Open Live Script

Display the impulse and frequency responses of a frequency-selective multipath Rayleigh fading channel that is configured to disable channel filtering.

Define simulation variables. Specify path delays and gains by using the ITU pedestrian B channel configuration.

fs = 3.84e6;% Sample rate in HzpathDelays = [0 200 800 1200 2300 3700]*1e-9;% in secondsavgPathGains = [0 -0.9 -4.9 -8 -7.8 -23.9];% dBfD = 50;% Max Doppler shift in Hz

Create a multipath Rayleigh fading channel System object to visualize the impulse response and frequency response plots.

rayleighchan = comm.RayleighChannel('SampleRate',fs,...'PathDelays',pathDelays,...'AveragePathGains',avgPathGains,...'MaximumDopplerShift',fD,...'ChannelFiltering',false,...'Visualization','Impulse and frequency responses');

Visualize the channel response by running the multipath Rayleigh fading channel System object with no input signal. The impulse response plot enables you to identify the individual paths and their corresponding filter coefficients. The frequency response plot shows the frequency-selective nature of the ITU pedestrian B channel.

rayleighchan();

Open Live Script

Show that the channel state is maintained for discontinuous transmissions by using multipath Rayleigh fading channel System objects that use the sum-of-sinusoids technique. Observe discontinuous channel response segments overlaid on a continuous channel response.

Set the channel properties.

fs = 1000;% Sample rate (Hz)pathDelays = [0 2.5e-3];% In secondspathPower = [0 -6];% In dBfD = 5;% Maximum Doppler shift (Hz)ns = 1000;% Number of samplesnsdel = 100;% Number of samples for delayed paths

Define a continuous time span and three discontinuous time segments over which to plot and view the channel response. View a 1000-sample continuous channel response that starts at time 0 and three 100-sample channel responses that start at times 0.1, 0.4, and 0.7 seconds, respectively.

to0 = 0.0; to1 = 0.1; to2 = 0.4; to3 = 0.7; t0 = (to0:ns-1)/fs;% Transmission 0t1 = to1+(0:nsdel-1)/fs;% Transmission 1t2 = to2+(0:nsdel-1)/fs;% Transmission 2t3 = to3+(0:nsdel-1)/fs;% Transmission 3

Create a frequency-flat multipath Rayleigh fading System object, specifying a 1000 Hz sampling rate, the sum-of-sinusoids fading technique, disabled channel filtering, and the number of samples to view. Specify a seed value so that results can be repeated. Use the defaultInitialTimeproperty setting so that the fading channel is simulated from time 0.

rayleighchan1 = comm.RayleighChannel('SampleRate',fs,...'MaximumDopplerShift',fD,...'RandomStream','mt19937ar with seed',...'Seed',17,...'FadingTechnique','Sum of sinusoids',...'ChannelFiltering',false,...'NumSamples',ns);

Create a clone of the multipath Rayleigh fading channel System object. In the cloned object, set the number of samples to view for the delayed paths. Also configure the initial time source as an input so that you can specify the fading channel offset time as an input argument when using the System object.

rayleighchan2 = clone(rayleighchan1); rayleighchan2.NumSamples = nsdel; rayleighchan2.InitialTimeSource ='Input port';

Save the path gain output for the continuous channel response by using therayleighchan1object and for the discontinuous delayed channel responses by using therayleighchan2object with initial time offsets are provided as input arguments.

pg0 = rayleighchan1(); pg1 = rayleighchan2(to1); pg2 = rayleighchan2(to2); pg3 = rayleighchan2(to3);

Compare the number of samples processed by the two channels by using the我nfoobject function. Therayleighchan1object processed 1000 samples, while therayleighchan2object processed only 300 samples.

G = info(rayleighchan1); H = info(rayleighchan2); [G.NumSamplesProcessed H.NumSamplesProcessed]
ans =1×21000 300

Convert the path gains into decibels.

pathGain0 = 20*log10(abs(pg0)); pathGain1 = 20*log10(abs(pg1)); pathGain2 = 20*log10(abs(pg2)); pathGain3 = 20*log10(abs(pg3));

Plot the path gains for the continuous and discontinuous cases. The gains for the three segments match the gain for the continuous case. Because the channel characteristics are maintained even when data is not transmitted, the alignment of the two plots shows that the sum-of-sinusoids technique is suited to the simulation of packetized data.

plot(t0,pathGain0,'r--') holdonplot(t1,pathGain1,'b') plot(t2,pathGain2,'b') plot(t3,pathGain3,'b') grid xlabel('Time (sec)') ylabel('Path Gain (dB)') legend('Continuous','Discontinuous','location','nw') title('Continuous and Discontinuous Transmission Path Gains')

图包含一个坐标轴对象。坐标轴对象with title Continuous and Discontinuous Transmission Path Gains, xlabel Time (sec), ylabel Path Gain (dB) contains 4 objects of type line. These objects represent Continuous, Discontinuous.

Open Live Script

Reproduce the multipath Rayleigh fading channel output across multiple frames by using theChannelFilterCoefficientsproperty returned by the info object function of thecomm.RayleighChannelSystem object.

Create a multipath Rayleigh fading channel System object, defining two paths. Generate data to pass through the channel.

rayleighchan = comm.RayleighChannel(...'SampleRate',1000,...'PathDelays',[0 1.5e-3],...'AveragePathGains',[0 -3],...'PathGainsOutputPort',true)
rayleighchan = comm.RayleighChannel with properties: SampleRate: 1000 PathDelays: [0 0.0015] AveragePathGains: [0 -3] NormalizePathGains: true MaximumDopplerShift: 1.0000e-03 DopplerSpectrum: [1x1 struct] ChannelFiltering: true PathGainsOutputPort: true Show all properties
data = randi([0 1],600,1);

Pass data through the channel. Assign theChannelFilterCoefficientsproperty value to the variablecoeff. Within aforloop, calculate the fractional delayed input signal at the path delay locations stored incoeff, apply the path gains, and sum the results for all of the paths. Compare the output of the multipath Rayleigh fading channel System object (查nout1) to the output reproduced using the path gains and theChannelFilterCoefficientsproperty of the multipath Rayleigh fading channel System object (查nout2).

查ninfo = info(rayleighchan); coeff = chaninfo.ChannelFilterCoefficients; Np = length(rayleighchan.PathDelays); state = zeros(size(coeff,2)-1,size(coeff,1)); nFrames = 10; chkChan = zeros(nFrames,1);forjj = 1 : nFrames data = randi([0 1],600,1); [chanout1,pg] = rayleighchan(data); fracdelaydata = zeros(size(data,1),Np);% Calculate the fractional delayed input signal.for我我= 1:Np [fracdelaydata(:,ii),state(:,ii)] =...filter(coeff(ii,:),1,data,state(:,ii));end% Apply the path gains and sum the results for all of the paths.% Compare the channel outputs.查nout2 = sum(pg .* fracdelaydata,2); chkChan(jj) = isequal(chanout1,chanout2);endchkChan'
ans =1×101 1 1 1 1 1 1 1 1 1
Open Live Script

Verify that the autocorrelation of the path gain output from the Rayleigh channel System object is a Bessel function. The results in[ 1 ]and Appendix A of[ 2 ], show that when the autocorrelation of the path gain outputs is a Bessel function, the Doppler spectrum is Jakes-shaped.

Initialize simulation parameters.

Rsym = 9600;% Input symbol rate (symbols/s)sps = 10;% Number of samples per input symbolFs = sps*Rsym;% Input sampling frequency (samples/s)Ts = 1/Fs;% Input sampling period (s)numsym = 1e6;% Number of input symbols to simulatenumsamp = numsym*sps;% Number of channel samples to simulatefd = 100;% Maximum Doppler frequency shift (Hz)num_acsamp = 5000;% Number of samples of autocovariance% of complex fading process calculatednumtx = 1;% Number of transmit antennasnumrx = 1;% Number of receive antennasnumsin = 48;% Number of sinusoidsfrmLen = 10000; numFrames = numsamp/frmLen;

Configure a Rayleigh channel System object.

查n = comm.RayleighChannel(...'FadingTechnique','Sum of sinusoids',...'NumSinusoids',numsin,...'RandomStream','mt19937ar with seed',...'PathDelays',0,...'AveragePathGains',0,...'SampleRate',Fs,...'MaximumDopplerShift',fd,...'PathGainsOutputPort',true);

Apply DPSK modulation to a random bit stream.

tx = randi([0 1],numsamp,numtx);% Random bit streamdpskSig = dpskmod(tx,2);% DPSK signal

Pass the modulated signal through the channel.

outsig = zeros(numsamp,numrx); pg_rx = zeros(numsamp,numrx,numtx);forfrmNum = 1:numFrames [outsig((1:frmLen)+(frmNum-1)*frmLen,:),pathGains] =...查n(dpskSig((1:frmLen)+(frmNum-1)*frmLen,:));for我= 1:numrx pg_rx((1:frmLen)+(frmNum-1)*frmLen,i,:) =...pathGains(:,:,:,i);endend

Using the channel path gains received per antenna, compute the autocovariance of the fading process for each transmit-receive path.

autocov = zeros(frmLen+1,numrx,numtx); autocov_normalized_real = zeros(num_acsamp+1,numrx,numtx); autocov_normalized_imag = zeros(num_acsamp+1,numrx,numtx);for我= 1:numrx% Compute autocovariance of simulated complex fading processforj = 1:numtx autocov(:,i,j) = xcov(pg_rx(:,i,j),num_acsamp);% Real part of normalized autocovarianceautocov_normalized_real(:,i,j) =...real(autocov(num_acsamp+1:end,i,j).../ autocov(num_acsamp+1,i,j));% Imaginary part of normalized autocovarianceautocov_normalized_imag(:,i,j) =...我mag(autocov(num_acsamp+1:end,i,j).../ autocov(num_acsamp+1,i,j));endend

Compute the theoretical autocovariance of the complex fading process by using thebesseljfunction.

Rrr = zeros(1,num_acsamp+1);forn = 1:1:num_acsamp+1 Rrr(n) = besselj(0,2*pi*fd*(n-1)*Ts);endRrr_normalized = Rrr/Rrr(1);

Display the autocovariance to compare the results from the Rayleigh channel System object and thebesseljfunction.

subplot(2,1,1) plot(autocov_normalized_real,'b-') holdonplot(Rrr_normalized,'r-') holdofflegend('comm.RayleighChannel',...'Bessel function of the first kind') title('Autocovariance of Real Part of Rayleigh Process') subplot(2,1,2) plot(autocov_normalized_imag) legend('comm.RayleighChannel') title('Autocovariance of Imaginary Part of Rayleigh Process')

Figure contains 2 axes objects. Axes object 1 with title Autocovariance of Real Part of Rayleigh Process contains 2 objects of type line. These objects represent comm.RayleighChannel, Bessel function of the first kind. Axes object 2 with title Autocovariance of Imaginary Part of Rayleigh Process contains an object of type line. This object represents comm.RayleighChannel.

As computed below, the mean square error comparing the results from the Rayleigh channel object versus the Bessel function is insignificant.

act_mse_real =...sum((autocov_normalized_real-repmat(Rrr_normalized.',1,numrx,numtx)).^2,1).../ size(autocov_normalized_real,1)
act_mse_real = 7.0043e-08
act_mse_imag = sum((autocov_normalized_imag-0).^2,1).../ size(autocov_normalized_imag,1)
act_mse_imag = 4.1064e-07

References

1. Dent, P., G.E. Bottomley, and T. Croft. “Jakes Fading Model Revisited.”Electronics Letters29, no. 13 (1993): 1162. https://doi.org/10.1049/el:19930777.

2. Pätzold, Matthias.Mobile Fading Channels. Chichester, UK: John Wiley & Sons, Ltd, 2002. https://doi.org/10.1002/0470847808.

This example uses:

Open Live Script

Compute and plot the empirical and theoretical probability density function (PDF) for a Rayleigh channel with one path.

Initialize parameters and create a Rayleigh channel System object that does not apply channel filtering.

Ns = 1.92 e6;Rs = 1.92 e6;dopplerShift = 2000;查n = comm.RayleighChannel(...'SampleRate',Rs,...'PathDelays',0,...'AveragePathGains',0,...'MaximumDopplerShift',dopplerShift,...'ChannelFiltering',false,...'NumSamples',Ns,...'FadingTechnique','Sum of sinusoids');

Compute and plot the empirical and theoretical PDF for the Rayleigh channel, by using thefitdist(Statistics and Machine Learning Toolbox)andpdf(Statistics and Machine Learning Toolbox)functions.

figure; holdon;% Empirical PDF plotgain = chan(); pd = fitdist(abs(gain),'Kernel','BandWidth',.01); r = 0:.1:3; y = pdf(pd,r); plot(r,y)% Theoretical PDF plotexp_pdf_amplitude = raylpdf(r,0.7); plot(r,exp_pdf_amplitude') legend('Empirical','Theoretical') title('Empirical and Theoretical PDF Curves')

图包含一个坐标轴对象。坐标轴对象with title Empirical and Theoretical PDF Curves contains 2 objects of type line. These objects represent Empirical, Theoretical.

More About

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References

[1]Oestges, Claude, and Bruno Clerckx.MIMO Wireless Communications: From Real-World Propagation to Space-Time Code Design. 1st ed. Boston, MA: Elsevier, 2007.

[2]Correia, Luis M., and European Cooperation in the Field of Scientific and Technical Research (Organization), eds.Mobile Broadband Multimedia Networks: Techniques, Models and Tools for 4G. 1st ed. Amsterdam ; Boston: Elsevier/Academic Press, 2006.

[3]一般Kermoal, l·舒马赫K.I. Pedersen体育Mogensen, and F. Frederiksen. “A Stochastic MIMO Radio Channel Model with Experimental Validation.”IEEE Journal on Selected Areas in Communications20, no. 6 (August 2002): 1211–26. https://doi.org/10.1109/JSAC.2002.801223.

[4]Jeruchim, Michel C., Philip Balaban, and K. Sam Shanmugan.Simulation of Communication Systems. Second edition. Boston, MA: Springer US, 2000.

[5]Patzold, M., Cheng-Xiang Wang, and B. Hogstad. “Two New Sum-of-Sinusoids-Based Methods for the Efficient Generation of Multiple Uncorrelated Rayleigh Fading Waveforms.”IEEE Transactions on Wireless Communications8, no. 6 (June 2009): 3122–31. https://doi.org/10.1109/TWC.2009.080769.

Extended Capabilities

Version History

Introduced in R2013b

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See Also

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