2x2 MIMO Matlab Code | STBC Matlab Code

This page covers MIMO MATLAB code for OFDM modulation. The STBC matlab code for 2x1 MIMO and 2x2 MIMO configurations are mentioned.

Figure 1: STBC 2x1 MIMO configurations

Following is the script for 2x1 MIMO matlab code.

%code:Alamouti code 2x1 MIMO STBC matlab code
clc;
clear all;
close all;
ndata=2;   % number of randam data
x=randint(ndata,1,1); % input data generated
x=[1 2];
%y=[x];
%INPUT DATA BITS
Data_input_bit(1,1)=x(1,1)
Data_input_bit(1,2)=x(1,2)
figure;plot(Data_input_bit);title('input data bits');
%performing 4 qam modulation on the input data
z=qammod(Data_input_bit,4);
%CHANNEL COEFFICENTS MATRIX
h=[0.3 -.2];
%h11=1;  h12=1;
%h21=1;  h22=1;
%NOISE COEFFICENTS
e=[.1 .1];
%e11=1;  e12=1;
%e21=1;  e22=1;
out=zeros(10,1);
for i=1;%:ndata-1;
    % Symbols at time period T;
    out(i,1)=z(i);
    out(i+1,1)=z(i+1);
    % Symbols at time period T+1;
    out(i,2)=-conj(z(i+1));
    out(i+1,2)=conj(z(i));
    %time_t2(i,1)=-conj(z(i+1));
    %time_t2(i+1,1)=conj(z(i));
end
s1=out(i,1);
s2=out(i+1,1);
%for j=1:100
for i=1;
    %Recieved data by RX1 Antenna at time interval T
    r(1,1)= (h(1,1)*s1)               +  (h(1,2)*s2)           + e(1,1);
    %Recieved data by RX1 Antenna at time interval (T+1)
    r(1,2)= ((-h(1,1))*conj(s2))      +  (h(1,2)*conj(s1))     + e(1,2);
end
t(1,1)=((conj(h(1,1))*r(1,1)));
t(1,2)=h(1,2)*(conj(r(1,2)));
t(2,1)=((conj(h(1,2)))*r(1,1));
t(2,2)=((h(1,1)*(conj(r(1,2)))));
%Maximum Likelehhod Detection Scehme
s1_e =t(1,1) + t(1,2);
s2_e= t(2,1) - t(2,2);
%s1_e= ((conj(h(1,1))*r(1,1))) + ((h(1,2)*(conj(r(1,2)))+ );
%s2_e= (((conj(h(2,1)))*r(2,1)) + ((h(1,2)*(conj(r(2,2))));
%performing 4 QAM Demodulation
%final output bits
final_output_Bits(1,1)=qamdemod(s1_e,4)
final_output_Bits(1,2)=qamdemod(s2_e,4)
figure;plot(final_output_Bits);title('final output Bits');

Figure 2: STBC 2x2 MIMO configurations

Following is the script for 2x2 MIMO matlab code.

%code:Alamouti code 2x2 MIMO STBC matlab code
clc;
clear all;
close all;
ndata=2;   % number of randam data
x=randint(ndata,1,1); % input data generated
x=[2 3];
%y=[x];
%INPUT DATA BITS
Data_input_bit(1,1)=x(1,1)
Data_input_bit(1,2)=x(1,2)
%performing 16 qam modulation on the input data
z=qammod(Data_input_bit,4);
%CHANNEL COEFFICENTS MATRIX
h=[0.3 -.2 ;.1 .11];
%h11=1;  h12=1;
%h21=1;  h22=1;
%NOISE COEFFICENTS
e=[.1 .1;.1 .1];
%e11=1;  e12=1;
%e21=1;  e22=1;
out=zeros(10,1);
for i=1;%:ndata-1;
    % Symbols at time period T;
    out(i,1)=z(i);
    out(i+1,1)=z(i+1);
    % Symbols at time period T+1;
    out(i,2)=-conj(z(i+1));
    out(i+1,2)=conj(z(i));
    %time_t2(i,1)=-conj(z(i+1));
    %time_t2(i+1,1)=conj(z(i));
end
s1=out(i,1);
s2=out(i+1,1);
%for j=1:100
for i=1;
    %Recieved data by RX1 Antenna at time interval T
    r(1,1)= (h(1,1)*s1)               +  (h(1,2)*s2)           + e(1,1);
    %Recieved data by RX1 Antenna at time interval (T+1)
    r(1,2)= ((-h(1,1))*conj(s2))      +  (h(1,2)*conj(s1))     + e(1,2);
    %Recieved data by RX2 Antenna at time interval T
    r(2,1)= (h(2,1)*s1)                +  (h(2,2)*s2)           + e(2,1);
    %Recieved data by RX1 Antenna at time interval (T+1)
    r(2,2)= ((-h(2,1))*conj(s2))       +  (h(2,2)*conj(s1))      + e(2,2);
end
t(1,1)=((conj(h(1,1))*r(1,1)));
t(1,2)=h(1,2)*(conj(r(1,2)));
t(2,1)=((conj(h(2,1)))*r(2,1));
t(2,2)=((h(1,2)*(conj(r(2,2)))));
c(1,1)= ((conj(h(1,2)))*r(1,1));
c(1,2)= h(1,1)*(conj(r(1,2)));
c(2,1)=  ((conj(h(2,2)))*r(2,1));
c(2,2)= ((h(2,1)*(conj(r(2,2)))));
%Maximum Likelehhod Detection Scehme
s1_e =t(1,1) + t(1,2) + t(2,1) + t(2,2);
s2_e= c(1,1) - c(1,2) + c(2,1) - c(2,2);
%s1_e= ((conj(h(1,1))*r(1,1))) + ((h(1,2)*(conj(r(1,2)))+ ((conj(h(2,1)))*r(2,1)) + ((h(1,2)*(conj(r(2,2)))));
%s2_e= ((conj(h(1,2)))*r(1,1)) - ((h(1,1)*(conj(r(1,2))))  + ((conj(h(2,2)))*r(2,1)) - ((h(2,1)*(conj(r(2,2)))));
%performing 16 QAM Demodulation
%final output bits
final_output_Bits(1,1)=qamdemod(s1_e,4)
final_output_Bits(1,2)=qamdemod(s2_e,4)