lms-nlms-rls-matlab

function [rlsser,rlsoutput]=testrls(snr,n1,n2,qam1) %%n1=500; %%n2=5000; delta=15; qam=round(qam1); %%snr=30; mu=0.4; l=35; channel=[0.5,1.2,1.5,-1]; switch qam case 4 sigam=sqrt(2);%%%QAM4 case 16 sigam=sqrt(10);%%%QAM16 case 64 sigam=sqrt(42);%%%QAM64 case 256 sigam=sqrt(170);%%%QAM64 end lamda=1;%%%% 1/lamda lamda=1/lamda; phi=0.08; sigam1=sqrt(norm(channel)^2/10^(snr/10)); %QPSK sigam2=sqrt(sigam^2*norm(channel)^2/10^(snr/10)); %QAM16 %noise v=zeros(1,n1+n2); v(1:n1)=(sigam1/sqrt(2))*(randn(1,n1)+1j*randn(1,n1)); v(n1+1:n1+n2)=(sigam2/sqrt(2))*(randn(1,n2)+1j*randn(1,n2)); %data s(1:n1)=(randi(2,1,n1)*sqrt(2)-sqrt(2)*3/2)+1j*(randi(2,1,n1)*sqrt(2)-sqrt(2)*3/2); train=zeros(1,n1+delta); train(delta+1:n1+delta)=s(1:n1); s(n1+1:n1+n2)=qammod(randi(qam,1,n2)-1,qam); y=filter(channel,1,s); r=y+v; w=zeros(l,1); u=zeros(1,l); e=zeros(1,n1+n2); k=zeros(l,1); p=1/phi*eye(l); for i= 1:n1+delta u=[r(i),u(1:l-1)]; ss(i)=u*w; d(i)=train(i); k=lamda*p*u'/(1+lamda*u*p*u'); e(i)=d(i)-ss(i); w=w+k*e(i); %%%%%%%% p=lamda*p-lamda*k*u*p; end nm=0; for i=n1+delta+1:n1+n2 u=[r(i),u(1:l-1)]; ss(i)=u*w; dd(i)=qammod(qamdemod(ss(i),qam),qam); d(i)=dd(i); k=lamda*p*u'/(1+lamda*u*p*u'); e(i)=d(i)-ss(i); w=w+k*e(i); %%%%%%%% p=lamda*p-lamda*k*u*p; i; if(dd(i)~=s(i-delta)) nm=nm+1; end end nm; %figure; %subplot(2,2,1); %plot(train(delta+1:n1+delta),'.'); %grid; %title('training sequence'); %subplot(222); %plot(s(n1+1:n1+n2),'.'); %grid; %title('Transmitted sequence'); %subplot(223); %plot(r(n1+delta+1:n1+n2),'.'); %grid; %title('Received sequence'); %subplot(224); %plot(ss(n1+delta+1:n1+n2),'.'); %grid; %title('Equalizer output'); rlsser=nm/(n2-delta); rlsoutput=ss(n1+delta+1:n1+n2); end