matlab_水声信道中基于LMS算法的自适应均衡,里面有调制、解调、自适应均衡等模块

b b M = 4; codeRate = 1/2; constlen = 7; k = log2(M); % 产生二进制数 Fd = 1; Fs = 4; N = Fs/Fd; numSymb = 5000; numPlot = 20; SNRpBitDemo =4; SNR = SNRpBitDemo + 10*log10(k); seed = [654321 123456]; rand('state', seed(1)); randn('state', seed(2)); msg_orig = randsrc(numSymb,1,[0:1]); %卷积编码前的二进制数图 figure(1) stem([0:numPlot-1], msg_orig(1:numPlot),'bx'); axis([ 0 numPlot -0.2 1.2]); xlabel('Time'); ylabel('Amplitude'); title('Binary Symbols Before Convolutional Encoding' ); % 卷积编码 constlen = [7]; codegen = [171 133]; tblen = 32; codeRate = 1/2; trel = poly2trellis(constlen, codegen); [msg_enc_bi]=convenc(msg_orig, trel); numEncPlot = numPlot ./ codeRate; tEnc = [0:numEncPlot-1] * codeRate; % 卷积编码图 figure(2) stem(tEnc, msg_enc_bi(1:length(tEnc)),'rx'); axis([ min(tEnc) max(tEnc) -0.2 1.2]); xlabel('Time'); ylabel('Amplitude'); title('Binary Symbols After Convolutional Encoding' ); %加训练序列 Lc=500; for j=1:Lc temp=rand; if temp<0.5 pn_seq(j)=0; else pn_seq(j)=1; end end x=msg_enc_bi' xx=[pn_seq x] xxx=xx' %QPSK调制 randn('state', seed(2)); [msg_enc]= bi2de(reshape(xxx, ... size(xxx,2)*k,size(xxx,1) / k)'); grayencod = bitxor([0:M-1],floor([0:M-1]/2)); msg_gr_enc = grayencod(msg_enc+1); msg_tx = dmodce(msg_gr_enc, Fd, [Fs, pi/4], 'psk', M); %进入AWGN信道 msg_rx = awgn(msg_tx, -7); numModPlot = numEncPlot * Fs ./ k; tMod = [0:numModPlot-1] ./ Fs .* k; figure(3) plot(tMod, real(msg_tx(1:length(tMod))),'c-', ... tMod, imag(msg_tx(1:length(tMod))),'m-'); axis([ min(tMod) max(tMod) -1.5 1.5]); xlabel('Time'); ylabel('Amplitude'); title('Encoded Symbols After QPSK Baseband Modulation' ); %QPSK解调 legend('In-phase','Quadrature',0); msg_gr_demod = ddemodce(msg_rx, Fd, [Fs, pi/4], 'psk', M); [dummy graydecod] = sort(grayencod); graydecod = graydecod - 1; msg_demod = graydecod(msg_gr_demod+1)'; msg_demod_bi = de2bi(msg_demod,k)' ; msg_demod_bi = msg_demod_bi(:); %解调后的图 figure(4) stem(tEnc, msg_demod_bi(1:numEncPlot),'bx'); axis([ 0 numPlot -0.2 1.2]); xlabel('Time'); ylabel('Amplitude'); title('Demodulated Symbols' ); %自适应均衡 y=msg_demod_bi'; L=length(y); K=15; delta=0.01; estimated_c=zeros(1,2*K+1); for i=1:Lc-2*K y_i=y(i:i+2*K); z_i=estimated_c*y_i'; e_i=pn_seq(i)-z_i; estimated_c=estimated_c+delta*e_i*y_i; mse(i)=e_i.^2; end %学习曲线 figure(5) p=1:470 plot(p,mse) axis([0,470,0,1]) %用LMS算法算出的抽头系数作为固定权值 test=y(1:470); equalized_test=filter(estimated_c,1,test); sequence_use=y(501:10500); equalized_x=filter(estimated_c,1,sequence_use); for t=1:10000 if equalized_x(t)<0.5 sign_out(t)=0; else sign_out(t)=1; end end %维特比译码硬判决 msg_dec = vitdec(sign_out, trel, tblen, 'cont', 'hard'); msg_dec=msg_dec'; %译码后的图 figure(6) stem([0:numPlot-1], msg_orig(1:numPlot),'rx'); hold on; stem([0:numPlot-1], msg_dec(1+tblen:numPlot+tblen),'bo'); hold off; axis([ 0 numPlot -0.2 1.2]); xlabel('Time'); ylabel('Amplitude'); title('Decoded Symbols' ); [errorBitCod ratioBitCod] = biterr(msg_enc, msg_demod); [errorBitCh ratioBitCh] = biterr(msg_orig(1:end-tblen), msg_dec(1+tblen:end));