How to simulate 16QAM Spatial Modulation by ML detection?

[q0206010]

I have 4QAM-Spatial Modulation matlabcode . But i need to simulate 4transmit antennas,4receive antennas 16QAM-SM By ML detection .How should i do

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clc 
clear all; 
N=3*10^5;                      %number of symbol 
symbol_set=[1+1i;1-1i;1i-1;1i-1i]/sqrt(2);   %set of symbol to be transmitted 
symbolset_size=4; 
symbol_size=N/3; 
Eb_No_Db=(0:25); 
nTx=2;                              % number of transmitting antenna 
nRx=2;                              % number of receiving antenna 
antennabits=[0;1]; 
Sym_to_bit=[0 0;0 1;1 0;1 1]; 
 
i=randi([0 1],1,N) ;    % generating stream of bits 
 
x=vec2mat(i,3);          % grouping generated bits into 3 
 
s=kron(symbol_set,ones(nRx,1));   % grouping symbols into matrix 
s=repmat(s,[1 nTx]); 
xTransmit=zeros(symbol_size,nTx);                                                              
xDemod=zeros(symbol_size,3);                                                                   
 
antenna_symbol=zeros(N/3,1);     
antenna_symbol(:,1)=x(:,1)+1;       %  
antenna_symbol(:,2)=symbol_set(bi2de(x(:,2:3),'left-msb')+1) ;   %Modulate 
 
for ii=1:length(Eb_No_Db) 
     
    for jj=1:symbol_size 
        
        h=1/sqrt(2)*(randn(nRx,nTx))+ 1i*(randn(nRx,nTx));    % rayleigh channel 
         
        n=1/sqrt(2)*(randn(nRx,1))+1i*(randn(nRx,1));            % noise 
         
    H=kron(ones(symbolset_size,1),h);       
      sD= H.*s; 
       
            xTransmit(jj,antenna_symbol(jj,1)) =antenna_symbol(jj,2) ;      % Assign Symbol and Antenna Index 
            xTransmit2=kron(xTransmit(jj,:),ones(nRx,1)); 
             
            y = sum(xTransmit2.*h,2) +10^(-Eb_No_Db(ii)/20)*n; 
             
            y2=kron(ones(symbolset_size,1),y);              % Copy for Symbol set 
            y2=repmat(y2,1,nRx);             % Copy for Antenna 
            y2=abs(y2-sD); 
 
            z=zeros(symbolset_size,nTx); 
            z(1,:)=abs(sum(y2(1:2,:),1)); 
            z(2,:)=abs(sum(y2(3:4,:),1)); 
            z(3,:)=abs(sum(y2(5:6,:),1)); 
            z(4,:)=abs(sum(y2(7:8,:),1)); 
            [v r]=min(z); 
            [v c]=min(v); 
            xDemod(jj,1)=antennabits(c); 
             
            xDemod(jj,2:3)=Sym_to_bit(r(c),:); 
       
    end 
     
    nErr(ii)= size(find(i-reshape(xDemod',1,[])),2); 
end 
simBER = nErr/N; 
 
 
close all 
figure 
semilogy(Eb_No_Db,simBER,'m.-','linewidth',2); 
axis([0 20 10^-5 1]) 
grid on 
legend('Sim 4QAM'); 
xlabel('Eb/No, dB') 
ylabel('Bit Error Rate') 
title('Bit Error Prob 4QAM 2x2 (3 Bit) with SM in Rayleigh Fading')

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[pythonista]

FYI, the following implementation includes the ML-aided spatial modulation scheme with QPSK, where the number of transmit and receiver antennas is 4, although it uses Python. You can reproduce that simulation result by changing "L=4_mod=PSK" to "L=16_mod=QAM".

https://ishikawa.cc/imtoolkit/tutorial/CoherentMIMO-IdealRayleigh-BER.html