SF-FDMA.rar_fdma_sf_matlab

%=================================== % This is the simulator for SC-FDMA. %=================================== function [SER ifdma SER lfdma] = scfdma(SP) numSymbols = SP.FFTsize; % The number of transmitted SC-FDMA symbols. Q = numSymbols/SP.inputBlockSize; % The bandwidth spreading factor. % Frequency domain version of the channel response. H_channel = fft(SP.channel,SP.FFTsize); for n = 1:length(SP.SNR), % Initialize the error count. errCount_ifdma = 0; errCount_lfdma = 0; for k = 1:SP.numRun, % Generate random data block. tmp = round(rand(2,SP.inputBlockSize)); tmp = tmp*2 - 1; inputSymbols = (tmp(1,:) + i*tmp(2,:))/sqrt(2); % DFT-precoding. inputSymbols_freq = fft(inputSymbols); % Initialize the output subcarriers. inputSamples_ifdma = zeros(1,numSymbols); inputSamples_lfdma = zeros(1,numSymbols); % Subcarrier mapping. % Interleaved (distributed) mapping. inputSamples_ifdma(1+SP.subband:Q:numSymbols) = inputSymbols_freq; % Localized mapping. inputSamples_lfdma([1:SP.inputBlockSize]+SP.inputBlockSize*SP.subband) = inputSymbols_freq; % Convert the signal back to time domain. inputSamples_ifdma = ifft(inputSamples_ifdma); inputSamples_lfdma = ifft(inputSamples_lfdma); % Add CP. TxSamples_ifdma = [inputSamples_ifdma(numSymbols - SP.CPsize+1:numSymbols) inputSamples_ifdma]; TxSamples_lfdma = [inputSamples_lfdma(numSymbols - SP.CPsize+1:numSymbols) inputSamples_lfdma]; % Propagate through multi-path channel. RxSamples_ifdma = filter(SP.channel, 1, TxSamples_ifdma); RxSamples_lfdma = filter(SP.channel, 1, TxSamples_lfdma); % Generate AWGN with appropriate noise power. tmp = randn(2, numSymbols+SP.CPsize); complexNoise = (tmp(1,:) + i*tmp(2,:))/sqrt(2); noisePower = 10^(-SP.SNR(n)/10); % Add AWGN to the transmitted signal. RxSamples_ifdma = RxSamples_ifdma + sqrt(noisePower/Q)*complexNoise; RxSamples_lfdma = RxSamples_lfdma + sqrt(noisePower/Q)*complexNoise; % Remove CP. RxSamples_ifdma = RxSamples_ifdma(SP.CPsize+1:numSymbols+SP.CPsize); RxSamples_lfdma = RxSamples_lfdma(SP.CPsize+1:numSymbols+SP.CPsize); % Convert the received signal into frequency domain. Y_ifdma = fft(RxSamples_ifdma, SP.FFTsize); Y_lfdma = fft(RxSamples_lfdma, SP.FFTsize); % Subcarrier de-mapping. Y_ifdma = Y_ifdma(1+SP.subband:Q:numSymbols); Y_lfdma = Y_lfdma([1:SP.inputBlockSize]+SP.inputBlockSize*SP.subband); % Find the channel response for the interleaved subcarriers. H_eff = H_ channel(1+SP.subband:Q:numSymbols); % Perform channel equalization in the frequency domain. if SP.equalizerType == 'ZERO' Y_ifdma = Y_ifdma./H_eff; elseif SP.equalizerType == 'MMSE' C = conj(H_eff)./(conj(H_eff).*H_eff + 10^(-SP.SNR(n)/10)); Y_ifdma = Y_ifdma.*C; end % Find the channel response for the localized subcarriers. H_eff = H_channel([1:SP.inputBlockSize]+SP.inputBlockSize*SP.subband); % Perform channel equalization in the frequency domain. if SP.equalizerType == 'ZERO' Y_lfdma = Y_lfdma./H_eff; elseif SP.equalizerType == 'MMSE' C = conj(H_eff)./(conj(H_eff).*H_eff + 10^(-SP.SNR(n)/10)); Y_lfdma = Y_lfdma.*C; end % Convert the signal back to time domain. EstSymbols_ifdma = ifft(Y_ifdma); EstSymbols_lfdma = ifft(Y_lfdma); % Perform hard decision detection. EstSymbols_ifdma = sign(real(EstSymbols_ifdma)) + i*sign(imag(EstSymbols_ifdma)); EstSymbols_ifdma = EstSymbols_ifdma/sqrt(2); EstSymbols_lfdma = sign(real(EstSymbols_lfdma)) + i*sign(imag(EstSymbols_lfdma)); EstSymbols_lfdma = EstSymbols_lfdma/sqrt(2); % Find and count errors. I_ifdma = find((inputSymbols-EstSymbols_ifdma) == 0); errCount_ifdma = errCount_ifdma + (SP.inputBlockSize-length(I_ifdma)); I_lfdma = find((inputSymbols-EstSymbols_lfdma) == 0); errCount_lfdma = errCount_lfdma + (SP.inputBlockSize-length(I_lfdma)); end % Calculate the symbol error rate (SER). SER_ifdma(n,:) = errCount_ifdma /(SP.inputBlockSize*SP.numRun); SER_lfdma(n,:) = errCount_lfdma /(SP.inputBlockSize*SP.numRun); end