Feedback diversity system in Wireless communication

Can anyone tell a way to create a simulation to depict the feedback diversity system wireless communication using matlab 2023

Answer 1

[Saurav]

Hi @Hemaakanth Natkunarajah,

I understand that you want to develop a simulation to demonstrate the feedback diversity system concept in wireless communication using MATLAB R2023.

Here is a sample code whose parameters can be tweaked according to the needs.

% Parameters
numBits = 1e7; % Number of bits to transmit
SNRdB = 0:2:20; % SNR range in dB
numDiversityBranches = 2; % Number of diversity branches

% Generate random bits
dataBits = randi([0 1], numBits, 1);

% BPSK Modulation
txSymbols = 2*dataBits - 1; % BPSK symbols: 0 -> -1, 1 -> 1

% Rayleigh Fading Channel
h = (randn(numBits, numDiversityBranches) + 1i*randn(numBits, numDiversityBranches)) / sqrt(2);

% Add AWGN Noise
noise = (randn(numBits, numDiversityBranches) + 1i*randn(numBits, numDiversityBranches)) / sqrt(2);

% Initialize BER array
BER = zeros(length(SNRdB), 1);

for idx = 1:length(SNRdB)
    SNR = 10^(SNRdB(idx)/10); % Convert SNR from dB to linear scale
    
    % Channel and noise scaling based on SNR
    rxSymbols = h .* repmat(txSymbols, 1, numDiversityBranches) + (1/sqrt(SNR)) * noise;
    
    % Calculate the combined SNR for MRC
    combinedSNR = sum(abs(h).^2, 2) * SNR;
    
    % Feedback: Receiver sends combined SNR back to the transmitter
    % (Here, we assume perfect feedback with no delay or error)
    
    % Transmitter adjusts power based on feedback
    % For simplicity, let's assume the transmitter scales its power by the combined SNR
    adjustedTxSymbols = txSymbols .* sqrt(combinedSNR);
    
    % Recompute received symbols with adjusted power
    rxSymbols = h .* repmat(adjustedTxSymbols, 1, numDiversityBranches) + (1/sqrt(SNR)) * noise;
    
    % Maximal Ratio Combining (MRC)
    combinedSymbols = sum(conj(h) .* rxSymbols, 2) ./ sum(abs(h).^2, 2);
    
    % Decision
    rxBits = real(combinedSymbols) > 0;
    
    % Calculate Bit Error Rate (BER)
    BER(idx) = sum(rxBits ~= dataBits) / numBits;
end
% Plot BER vs. SNR
figure;
semilogy(SNRdB, BER, 'b-o', 'LineWidth', 2);
grid on;
xlabel('SNR (dB)');
ylabel('Bit Error Rate (BER)');
title('BER vs. SNR for Feedback Diversity System');
legend('Maximal Ratio Combining with Feedback');

Note: The provided sample code utilizes Maximal Ratio Combining (MRC) as the combining technique. However, other combining techniques and different numbers of diversity branches can be implemented with appropriate modifications to depict feedback diversity.

I hope this helps.