Beamforming MATLAB Code for QAM Modulation

This page provides MATLAB source code for Beamforming. It includes output plots and mathematical equations related to Beamforming with QAM modulation.

QAM stands for Quadrature Amplitude Modulation.

Introduction to Beamforming

Beamforming is a technique used to enhance signal strength before transmission using multiple antenna arrays. It helps extend the coverage of cell towers to reach mobile subscribers further away.

The main types of beamforming techniques are:

• Analog Beamforming
• Digital Beamforming
• Hybrid Beamforming

Figure 1: Analog Beamforming Transmitter Block Diagram

Beamforming MATLAB Code

clear
N = 10^6;
nTx = 2;
M=4;
k = sqrt(1/((2/3)*(M-1)));
m = [1:sqrt(M)/2];
alphaMqam = [-(2*m-1) 2*m-1];
Eb_N0_dB = [0:30];
ipHat1 = zeros(1,N);
ipHat2 = zeros(1,N);

for ii = 1:length(Eb_N0_dB)
    ip = randsrc(1,N,alphaMqam) + j*randsrc(1,N,alphaMqam);
    s = k*ip;  % normalization of energy to 1
    n = 1/sqrt(2)*[randn(1,N) + j*randn(1,N)];  % white guassian noise, 0dB variance
    h = 1/sqrt(2)*[randn(nTx,N) + j*randn(nTx,N)];  % Rayleigh channel
    sr = (1/sqrt(nTx))*kron(ones(nTx,1),s);  % Channel and noise Noise addition
    h_tx = h.*exp(-j*angle(h));
    y1 = sum(h.*sr,1) + 10^(-Eb_N0_dB(ii)/20)*n;
    y2 = sum(h_tx.*sr,1) + 10^(-Eb_N0_dB(ii)/20)*n;
    y1Hat = y1./sum(h,1);
    y2Hat = y2./sum(h_tx,1);

    % demodulation
    y_re1 = real(y1Hat)/k;  % real part
    y_im1 = imag(y1Hat)/k;
    y_re2 = real(y2Hat)/k;  % real part
    y_im2 = imag(y2Hat)/k;  % imaginary part

    ipHat_re1 = 2*floor(y_re1/2)+1;
    ipHat_re1(find(ipHat_re1>max(alphaMqam))) = max(alphaMqam);
    ipHat_re1(find(ipHat_re1<min(alphaMqam))) = min(alphaMqam);
    ipHat_re2 = 2*floor(y_re2/2)+1;
    ipHat_re2(find(ipHat_re2>max(alphaMqam))) = max(alphaMqam);
    ipHat_re2(find(ipHat_re2<min(alphaMqam))) = min(alphaMqam);
    ipHat_im1 = 2*floor(y_im1/2)+1;
    ipHat_im1(find(ipHat_im1>max(alphaMqam))) = max(alphaMqam);
    ipHat_im1(find(ipHat_im1<min(alphaMqam))) = min(alphaMqam);
    ipHat_im2 = 2*floor(y_im2/2)+1;
    ipHat_im2(find(ipHat_im2>max(alphaMqam))) = max(alphaMqam);
    ipHat_im2(find(ipHat_im2<min(alphaMqam))) = min(alphaMqam);

    ipHat1 = ipHat_re1 + j*ipHat_im1;
    nErr1(ii) = size(find([ip- ipHat1]),2);  % counting the number of errors
    ipHat2 = ipHat_re2 + j*ipHat_im2;
    nErr2(ii) = size(find([ip- ipHat2]),2);  % counting the number of errors
end

simBer1 = nErr1/N;  % simulated ber (no beam forming)
simBer2 = nErr2/N;  % simulated ber (with beam forming)
theoryBerAWGN = 0.5*erfc(sqrt(10.^(Eb_N0_dB/10)));  % theoretical ber
EbN0Lin = 10.^(Eb_N0_dB/10);
theoryBer = 0.5.*(1-sqrt(EbN0Lin./(EbN0Lin+1)));
p = 1/2 - 1/2*(1+1./EbN0Lin).^(-1/2);
theoryBer_nRx2 = p.^2.*(1+2*(1-p));

close all
figure
semilogy(Eb_N0_dB,simBer1,'ks-','LineWidth',2);
hold on
semilogy(Eb_N0_dB,simBer2,'rx-','LineWidth',2);
axis([0 35 10^-5 0.5])
grid on
legend('2Tx-1Rx (no Beamforming-sim)','2Tx-1Rx (Beamforming-sim)');
xlabel('Eb/No, dB');
ylabel('Bit Error Rate');
title('BER for QAM modulation in Rayleigh Fading channel');

Input and Output of Beamforming QAM MATLAB Source Code

Run the downloaded BeamformingQAM.m file after extracting the contents of the folder.

The output MATLAB image will look similar to this: