Hi Lavish,

Here the matlab code for Approximate message passing (AMP) for Massive MIMO detection.

function main()

clc;clear; close all;

m=256;% # of received antennas

n=32;% # of users

SNRrange=[1:20];

count=0;

for s=SNRrange

SNRdb=s;

for monte=1:1000

x=(2*randi([0,1],n,1)-ones(n,1))+sqrt(-1)*(2*randi([0,1],n,1)-ones(n,1));

sigmas2=2;%signal variance in QPSK

H=1/sqrt(2*m)*randn(m,n)+sqrt(-1)/sqrt(2*m)*randn(m,n);

sigma2=2*n/m*10^(-SNRdb/10); %noise variance in control by SNR in DB

w=sqrt(2*sigma2)*randn(m,1)+sqrt(-1)*sqrt(2*sigma2)*randn(m,1);

y=H*x+w; %channel model

%iterAMP is # of iterations in AMP

iterAMP1=2;

xhat1=AMP(y,H,sigma2,sigmas2,iterAMP1,m,n);

iterAMP2=4;

xhat2=AMP(y,H,sigma2,sigmas2,iterAMP2,m,n);

x_mmse=(sigma2/sigmas2*eye(n)+H'*H)^(-1)*H'*y;

x_mmse=sign(real(x_mmse))+sqrt(-1)*sign(imag(x_mmse));

errorAMP1(monte)=sum(x~=xhat1);

errorAMP2(monte)=sum(x~=xhat2);

errorMMSE(monte)=sum(x~=x_mmse);

end

count=count+1;

serAMP1(count)=mean(errorAMP1);

serAMP2(count)=mean(errorAMP2);

serMMSE(count)=mean(errorMMSE);

end

figure(1)% plot the SER

semilogy(SNRrange,serAMP1,'-+r', SNRrange,serAMP2,'-pk',SNRrange, serMMSE,'-ob');

grid on;

legend(['AMP iteration=' int2str(iterAMP1)], ['AMP iteration=' int2str(iterAMP2)], 'MMSE');

xlabel('SNR (dB)'); ylabel('SER');

title(['BER performance comparison in system m= ' int2str(m) ' n=' int2str(n)]);

end

function xhat=AMP(y,H,sigma2,sigmas2,iterAMP,m,n)

% AMP detector in Massive MIMO

r=zeros(m,1);

xhat=zeros(n,1);

alpha=sigmas2;%initial estimation variance

for t=1:iterAMP

r=y-H*xhat+(n/m)*sigmas2/(sigmas2+alpha)*r;

alpha=sigma2+(n/m)*sigmas2*alpha/(sigmas2+alpha);

xhat=(sigmas2/(sigmas2+alpha))*(H'*r+xhat);

end

xhat=sign(real(xhat))+sqrt(-1)*sign(imag(xhat));

end

Hi, Lavish, tell me exactly what are you looking for. May be I can provide you the complete code.

Hi, Lavish, Gurjot is expert in massive mimo research field you can request him for the Code may be he will provide you some of his latest codes.