How can I simulate OFDM with Rayleigh fading by using Communications System Toolbox?

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QuestionAsker
QuestionAsker 2017-12-14
评论： Pablo Sanz 2022-4-12
I would like to adapt the example code in the following link such that the AWGN channel is preceded by a Rayleigh fading channel.
https://www.mathworks.com/help/comm/gs/qpsk-and-ofdm-with-matlab-system-objects-1.html
My code gives a bit-error rate of approximately 0.5, regardless of the signal-to-noise ratio. Could you please tell me what I am doing wrong?
M = 4; % Modulation alphabet
k = log2(M); % Bits/symbol
numSC = 128; % Number of OFDM subcarriers
cpLen = 32; % OFDM cyclic prefix length
maxBitErrors = 1e2; % Maximum number of bit errors
maxNumBits = 1e7; % Maximum number of bits transmitted
qpskMod = comm.QPSKModulator('BitInput',true);
qpskDemod = comm.QPSKDemodulator('BitOutput',true);
ofdmMod = comm.OFDMModulator('FFTLength',numSC,'CyclicPrefixLength',cpLen);
ofdmDemod = comm.OFDMDemodulator('FFTLength',numSC,'CyclicPrefixLength',cpLen);
rayleighChannel = comm.RayleighChannel;
awgnChannel = comm.AWGNChannel('NoiseMethod','Variance', 'VarianceSource','Input port');
errorRate = comm.ErrorRate('ResetInputPort',true);
ofdmDims = info(ofdmMod);
numDC = ofdmDims.DataInputSize(1);
frameSize = [k*numDC 1];
EbNoVec = (0:20)';
snrVec = EbNoVec + 10*log10(k) + 10*log10(numDC/numSC);
berVec = zeros(length(EbNoVec),3);
errorStats = zeros(1,3);
for m = 1:length(EbNoVec)
snr = snrVec(m);
while errorStats(2) <= maxBitErrors && errorStats(3) <= maxNumBits
dataIn = randi([0,1],frameSize); % Generate binary data
qpskTx = qpskMod(dataIn); % Apply QPSK modulation
txSig = ofdmMod(qpskTx); % Apply OFDM modulation
fadedSig = rayleighChannel(txSig);
powerDB = 10*log10(var(fadedSig)); % Calculate Tx signal power
noiseVar = 10.^(0.1*(powerDB-snr)); % Calculate the noise variance
rxSig = awgnChannel(fadedSig,noiseVar); % Pass the signal through a noisy channel
qpskRx = ofdmDemod(rxSig); % Apply OFDM demodulation
dataOut = qpskDemod(qpskRx); % Apply QPSK demodulation
errorStats = errorRate(dataIn,dataOut,0); % Collect error statistics
end
berVec(m,:) = errorStats; % Save BER data
errorStats = errorRate(dataIn,dataOut,1); % Reset the error rate calculator
end
berTheory = berawgn(EbNoVec,'psk',M,'nondiff');
berTheory_2 = berfading(EbNoVec,'psk',M,1);
figure
semilogy(EbNoVec,berVec(:,1),'*')
hold on
semilogy(EbNoVec,berTheory_2)
legend('Simulation','Theory','Location','Best')
xlabel('Eb/No (dB)')
ylabel('Bit Error Rate')
grid on
hold off

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回答（6 个）

Ahmed Aladi
Ahmed Aladi 2020-9-24
clear all;
M = 4; % Modulation alphabet
k = log2(M); % Bits/symbol
numSC = 128; % Number of OFDM subcarriers
cpLen = 32; % OFDM cyclic prefix length
maxBitErrors = 1e3; % Maximum number of bit errors
maxNumBits = 1e7; % Maximum number of bits transmitted
qpskMod = comm.QPSKModulator('BitInput',true);
qpskDemod = comm.QPSKDemodulator('BitOutput',true);
ofdmMod = comm.OFDMModulator('FFTLength',numSC,'CyclicPrefixLength',cpLen);
ofdmDemod = comm.OFDMDemodulator('FFTLength',numSC,'CyclicPrefixLength',cpLen);
awgnChannel = comm.AWGNChannel('NoiseMethod','Variance', 'VarianceSource','Input port');
errorRate = comm.ErrorRate('ResetInputPort',true);
ofdmDims = info(ofdmMod);
numDC = ofdmDims.DataInputSize(1);
frameSize = [k*numDC 1];
EbNoVec = (0:20)';
snrVec = EbNoVec + 10*log10(k) + 10*log10(numDC/numSC);
berVec = zeros(length(EbNoVec),3);
errorStats = zeros(1,3);
for m = 1:length(EbNoVec)
snr = snrVec(m);
while errorStats(2) <= maxBitErrors && errorStats(3) <= maxNumBits
dataIn = randi([0,1],frameSize); % Generate binary data
qpskTx = qpskMod(dataIn); % Apply QPSK modulation
txSig = ofdmMod(qpskTx); % Apply OFDM modulation
%fadedSig = rayleighChannel(txSig);
%% Rayleigh Fading Channel
taps=3; %number of channel taps
h = [randn(1,taps)+j*randn(1,taps) zeros(1,size(txSig,1)-taps)].' ; % generate channel taps and pad with zeros
h_t = toeplitz(h); % channel matrix
fadedSig=h_t*txSig; % Apply Rayleigh fading
powerDB = 10*log10(var(fadedSig)); % Calculate Tx signal power
noiseVar = 10.^(0.1*(powerDB-snr)); % Calculate the noise variance
rxSig = awgnChannel(fadedSig,noiseVar); % Pass the signal through a noisy channel
rxSig_eq = inv(h_t'*h_t)*(h_t')*rxSig; % zero forcing equalization
% Apply OFDM demodulation
qpskRx = ofdmDemod(rxSig_eq);
dataOut = qpskDemod(qpskRx); % Apply QPSK demodulation
errorStats = errorRate(dataIn,dataOut,0); % Collect error statistics
end
berVec(m,:) = errorStats; % Save BER data
errorStats = errorRate(dataIn,dataOut,1); % Reset the error rate calculator
end
berTheory = berawgn(EbNoVec,'psk',M,'nondiff');
berTheory_2 = berfading(EbNoVec,'psk',M,1);
figure
semilogy(EbNoVec,berVec(:,1),'*')
hold on
semilogy(EbNoVec,berTheory_2)
legend('Simulation','Theory','Location','Best')
xlabel('Eb/No (dB)')
ylabel('Bit Error Rate')
grid on
hold off
  6 个评论
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N/A
N/A 2020-9-9
I think the problem is when you generate the rayleigh channel, try to add some inputs such as the sampling time/frequency, the maximum doppler shift and you can add also the delays and there pdp,
Here is an exampe of how I simulate an EVA channel :
DS = 1e-9;
Tau = [0 30 150 310 370 710 1090 1730 2510]*DS;
Pdp = [0 -1.5 -1.4 -3.6 -0.6 -9.1 -7 -12 -16.9];
fd = 20/3.6*fc/c; % Maximum Doppler Shift
chan = rayleighchan(Ts, fd, Tau, Pdp);
with Ts being the sampling time,
N/A
N/A 2019-7-8
Did you find the problem with your program ?
mustafa sami
mustafa sami 2020-2-15
Did you find the problem with your program ?
Yasantha Samarawickrama
I am encountering the same problem? Can you please share if you found the solution for this issue?
Yue Shang
Yue Shang 2021-8-5
Some thoughts on the solution using comm.RayleighChannel
  1. The frequency-flat fading channel just applies a gain to each sample to the channel. The gain is the second output of the comm.RayleighChannel object's step method, i.e., pathGains. So the time-domain equalization can be done as rxSig_eq=rxSig./pathGains for ZF or rxSig_eq = rxSig.*conj(pathGains)./(abs(pathGains).^2+noiseVar) for MMSE.
  2. Set the MaximumDopplerShift property of comm.RayleighChannel to a larger number such as 0.1 for the channel to vary more quickly so you have the channel's "average" behavior in a shorter period of time. As a result, the maxBitErrors can be reduced for a shorter simulation.
  3. For this frequency-flat fading channel, the time-domain equation is simpler. For a frequency-selective channel with multipath (when PathDelays and AveragePathGains properties of comm.RayleighChannel are vectors), using a frequency-domain equalization after OFDM demodulation is usually simpler. You can refer to the Indoor MIMO-OFDM Communication Link using Ray Tracing example and in particular the helperIndoorRayTracingRxProcessing function in it for how this can be done.

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