Digital Communication Systems Using Matlab And Simulink May 2026

% Plot results semilogy(EbNo_dB, ber, 'bo-'); grid on; xlabel('Eb/No (dB)'); ylabel('BER'); title('BPSK over AWGN Channel'); hold on; semilogy(EbNo_dB, berawgn(EbNo_dB, 'psk', M, 'nondiff'), 'r-'); legend('Simulated', 'Theoretical');

Introduction In the modern era of 5G, IoT, and satellite internet, digital communication systems form the invisible backbone of global connectivity. From streaming high-definition video to controlling a Mars rover, the reliability and efficiency of these systems depend on sophisticated design, rigorous simulation, and relentless optimization.

– Add AWGN with desired (E_b/N_0). If modeling multipath, insert a Multipath Rayleigh Fading block before AWGN. Digital Communication Systems Using Matlab And Simulink

% Parameters M = 2; % BPSK modulation order numBits = 1e5; % Number of bits EbNo_dB = 0:2:10; % SNR range ber = zeros(size(EbNo_dB)); for idx = 1:length(EbNo_dB) % Generate random bits data = randi([0 1], numBits, 1);

– Map each pair of bits to a complex symbol using the QPSK Modulator Baseband block. Set average power to 1. % Plot results semilogy(EbNo_dB, ber, 'bo-'); grid on;

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– Insert a Raised Cosine Transmit Filter with 50% roll-off. Oversample by 8 to avoid aliasing. If modeling multipath, insert a Multipath Rayleigh Fading

% Compute BER [~, ber(idx)] = biterr(data, rxBits); end