Communication Systems MATLAB Projects (25+ Ideas with Complete Code)

% 16-QAM Monte Carlo BER Simulation in AWGN
M = 16; k = log2(M); numBits = 2e5;
EbNo_vec = 0:2:16; ber_sim = zeros(size(EbNo_vec));

data = randi([0 1], numBits, 1);
tx_sym = qammod(data, M, 'InputType', 'bit', 'UnitAveragePower', true);

for i = 1:length(EbNo_vec)
    snr = EbNo_vec(i) + 10*log10(k);
    rx_sym = awgn(tx_sym, snr, 'measured');
    rx_bits = qamdemod(rx_sym, M, 'OutputType', 'bit', 'UnitAveragePower', true);
    [~, ber_sim(i)] = biterr(data, rx_bits);
end

ber_theory = berawgn(EbNo_vec, 'qam', M);
semilogy(EbNo_vec, ber_sim, 'bo-', EbNo_vec, ber_theory, 'r--', 'LineWidth', 1.5);
grid on; xlabel('Eb/N0 (dB)'); ylabel('Bit Error Rate (BER)');
legend('Empirical Monte Carlo', 'Theoretical Closed-Form');

% Design Non-Ideal Proportional Resonant (PR) Controller for MMC-HVDC
Kp = 2.5; Kr = 150; wc = 5; w0 = 2*pi*100; % Resonant at 2*f_grid (100 Hz)
s = tf('s');

% Non-ideal PR transfer function
G_PR = Kp + (2*Kr*wc*s)/(s^2 + 2*wc*s + w0^2);

% Open-loop and Closed-loop MMC Plant Model
L_arm = 0.05; R_arm = 0.8;
G_plant = 1/(L_arm*s + R_arm);
G_loop = feedback(G_PR*G_plant, 1);

figure; bode(G_PR, {10, 1000}); grid on;
title('Bode Diagram of 100 Hz Harmonic Resonant Controller');

% Basic OFDM Transmission with Multipath Channel & Equalization
N = 64;           % Subcarriers
CP = 16;          % Cyclic prefix length
bits = randi([0 1], N*2, 1);
qpsk_syms = pskmod(bits, 4, pi/4, 'InputType', 'bit');

% IFFT and Cyclic Prefix Insertion
time_sym = ifft(qpsk_syms, N);
tx_signal = [time_sym(end-CP+1:end); time_sym];

% 3-Tap Dispersive Channel + AWGN
h = [0.8; 0.4; 0.2];
rx_signal = filter(h, 1, tx_signal);
rx_noisy = awgn(rx_signal, 20, 'measured');

% Remove CP & FFT
rx_no_cp = rx_noisy(CP+1:end);
rx_freq = fft(rx_no_cp, N);

% Zero-Forcing Frequency-Domain Equalizer
H_channel = fft(h, N);
eq_syms = rx_freq ./ H_channel;
scatterplot(eq_syms); title('Equalized OFDM Constellation');

% 2x2 MIMO Spatial Multiplexing with Zero-Forcing Receiver
Nt = 2; Nr = 2; SNR_dB = 15; SNR_lin = 10^(SNR_dB/10);
H = (randn(Nr, Nt) + 1j*randn(Nr, Nt))/sqrt(2); % Complex Rayleigh Matrix

% Transmit 16-QAM Symbols across Nt antennas
s = qammod(randi([0 15], Nt, 1), 16, 'UnitAveragePower', true);
noise = (randn(Nr, 1) + 1j*randn(Nr, 1)) / sqrt(2*SNR_lin);
y = H*s + noise;

% Zero-Forcing Detection (Pseudo-Inverse)
W_zf = pinv(H);
s_hat_zf = W_zf * y;

% MMSE Detection
W_mmse = (H'*H + (1/SNR_lin)*eye(Nt)) \ H';
s_hat_mmse = W_mmse * y;

% Shannon Ergodic Capacity
C = log2(real(det(eye(Nr) + (SNR_lin/Nt)*(H*H'))));
fprintf('2x2 MIMO Channel Capacity: %.2f bits/s/Hz\n', C);

% Schmidl-Cox Timing and CFO Estimation for SDR Baseband
N = 64; % OFDM Symbol Size
train_half = (randn(N/2, 1) + 1j*randn(N/2, 1));
preamble = [train_half; train_half]; % Repetitive preamble

% Received Signal over SDR with timing offset d=30 and CFO
cfo = 0.04; % Normalized frequency offset
rx = [zeros(30,1); preamble .* exp(1j*2*pi*cfo*(0:N-1)')] + 0.05*randn(N+30, 1);

% Timing Metric Computation
P = zeros(length(rx)-N, 1); R = zeros(length(rx)-N, 1);
for d = 1:length(rx)-N
    r1 = rx(d : d+N/2-1);
    r2 = rx(d+N/2 : d+N-1);
    P(d) = sum(conj(r1) .* r2);
    R(d) = sum(abs(r2).^2);
end
M_d = (abs(P).^2) ./ (R.^2 + eps);
[~, est_start] = max(M_d);
est_cfo = angle(P(est_start)) / pi;
fprintf('Detected Packet Start: Sample %d | Estimated CFO: %.4f\n', est_start, est_cfo);

% 5G NR PDSCH Link Level Simulation
carrier = nrCarrierConfig('SubcarrierSpacing', 30, 'NSizeGrid', 51);
pdsch = nrPDSCHConfig('Modulation', '64QAM', 'NumLayers', 2);
pdsch.PRBSet = 0:50;

% Configure TDL Channel Model
tdl = nrTDLChannel('DelayProfile', 'TDL-C', 'DelaySpread', 300e-9, ...
                   'MaximumDopplerShift', 30, 'SampleRate', 30.72e6);

% Generate Waveform and Transmit
[txWaveform, info] = nrWaveformGenerator(carrier, pdsch);
rxWaveform = tdl(txWaveform);
rxNoisy = awgn(rxWaveform, 18, 'measured');
fprintf('Generated 5G NR Waveform: %d samples at 30.72 MSps\n', length(txWaveform));