mrc1x2.m

2x1 MRRC using BPSK

SNRdb=[0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30];                                                                  %The graph will be drawn using different SNR values.
for i=1:length(SNRdb)                                                                     %The Program will continue computing for these different values. 
    sigma=sqrt(10^(-SNRdb(i)/10));                                                              %N0 variance of the noise will be computed.
    Ber1(i)=0;
    
    for run=1:10000                                                                           %The choose of 'run' value is 
                                                                                                      %important at this point since it will help us to achieve realistic results
    s0=(sign(randn(1,100))+j*sign(randn(1,100)))./sqrt(2);                           %Transmitted signal is constructed   
    H0=((randn(1,100))+j*(randn(1,100)));
    H1=((randn(1,100))+j*(randn(1,100)));
    N0=(sigma*((randn(1,100))+j*(randn(1,100))))./sqrt(2);
    N1=(sigma*((randn(1,100))+j*(randn(1,100))))./sqrt(2);
    r0=H0.*s0+N0;
    r1=H1.*s0+N1;
    %ML
    Shat=conj(H0).*r0+conj(H1).*r1;
    
    S0hat=sign(real(Shat));
    S1hat=sign(imag(Shat));
    STas=(S0hat+j*S1hat)./sqrt(2);
    Error=(sum(s0~=STas));
    Ber1((i))=Ber1(i)+Error./(2*100);

    
    
    
    
    end
end
Ber1=Ber1/run
semilogy(SNRdb,Ber1,'-*');title('BER Characteristic of QPSK Modulated Signals for Different SNR');
xlabel('E_b/N_0 (dB)');ylabel('BER (P_e)');grid;