Channel Estimation in OFDM using Neural Networks.
5 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
I am trying to implement the following code, but i get lots of fluctuations in MSE vs SNR of Neural networks. Could anyone please help me in getting a smoother response.
The code is give below:
clc clear all
nCP = 8; %round(Tcp/Ts); nFFT = 32; NT = nFFT + nCP; F = dftmtx(nFFT)/sqrt(nFFT); MC = 2; EsNodB = 0:1:31; snr = 10.^(EsNodB/10); beta = 17/9; M = 16; modObj = modem.qammod(M); demodObj = modem.qamdemod(M); L = 5; for ii = 1:length(EsNodB) disp('EsN0dB is :'); disp(EsNodB(ii)); tic; ChMSE_LS = 0; error=zeros(1,32); err2=[] err1=[] for mc = 1:MC % Random channel taps g = randn(L,1)+1i*randn(L,1); g = g/norm(g); H = fft(g,nFFT); % generation of symbol X = randi([0 M-1],nFFT,1); %BPSK symbols XD = modulate(modObj,X)/sqrt(10); % normalizing symbol power x = F'*XD; %loading xout = [x(nFFT-nCP+1:nFFT);x]; % channel convolution and AWGN y = conv(xout,g); nt =randn(nFFT+nCP+L-1,1) + 1i*randn(nFFT+nCP+L-1,1); No = 10^(-EsNodB(ii)/10); y = y + sqrt(No/2)*nt; % Receiver processing y = y(nCP+1:NT); Y = F*y; % frequency doimain LS channel estimation HhatLS = Y./XD; ChMSE_LS = ChMSE_LS + ((H -HhatLS)'*(H-HhatLS))/nFFT; %for l=1:32 x1=abs(x); x2=x1'; y1=abs(Y); y2=y1'; net=newff(minmax(y2), [4,1], {'logsig','purelin', 'trainlm'}); net=init(net) net.trainparam.epochs=600; %No. of iterations net.trainparam.lr=0.01; [net,tr]=train(net,y2,x2) x_net = net(y2); error=(x2-x_net); %err1=sum(err) %err2(l)=err1/MC; dbstop if error % end end %inp=rand(1,4) %v=sim(net,inp) %plot(v); %l= v-inp;
ChEstLS(ii) = ChMSE_LS/MC; %error1(ii)=err/MC; err=error/MC; end toc figure, plot(err,'g'); legend('Error'); figure, % Channel estimation semilogy(EsNodB,abs(err),'b','LineWidth',2); hold on semilogy(EsNodB,ChEstLS,'r','LineWidth',2); hold on;grid on;xlabel('EsNodB'); ylabel('Channel MSE');
legend('NN', 'LS');
3 Kommentare
Antworten (0)
Siehe auch
Kategorien
Mehr zu Pattern Recognition and Classification finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!