QPSK Signal Simulation in AWGN Channel

This MATLAB code demonstrates the simulation of QPSK signals transmitted through an AWGN (Additive White Gaussian Noise) channel. The implementation includes the complete signal processing chain: from data generation to modulation, noise addition, demodulation, and error rate calculation.

The simulation begins by defining QPSK modulator and demodulator objects using MATLAB's Communication System Toolbox. We then configure the simulation parameters including the number of bits and corresponding symbols (since each QPSK symbol carries 2 bits).

```matlab

% Define QPSK modulator and demodulator using Communication System Toolbox

qpskModulator = comm.QPSKModulator;

qpskDemodulator = comm.QPSKDemodulator;

% Configure simulation parameters: total bits and corresponding symbols

numBits = 100000;

numSymbols = numBits/2; % Each QPSK symbol represents 2 bits

% Generate random binary data and perform QPSK modulation

data = randi([0 1],numBits,1);

qpskSignal = qpskModulator(data);

% Add AWGN to simulate realistic channel conditions

SNR = 10; % Signal-to-Noise Ratio in dB

awgnSignal = awgn(qpskSignal,SNR,'measured'); % 'measured' option calculates signal power automatically

% Demodulate the noisy signal and compute Bit Error Rate (BER)

receivedData = qpskDemodulator(awgnSignal);

BER = comm.ErrorRate; % Create BER calculation object

errorStats = BER(data,receivedData); % Compare original and received data

fprintf('Bit Error Rate = %fn',errorStats(1))

```

The key algorithm involves comparing transmitted and received bits to calculate the Bit Error Rate (BER), which serves as a crucial performance metric for evaluating communication system robustness under noisy conditions. The 'awgn' function adds Gaussian noise with specified SNR, while the error rate calculation provides statistical performance analysis.