MATLAB Implementation of Gaussian Channel Simulation with BER Analysis

To simulate a Gaussian channel and thoroughly analyze the relationship between bit error rate and signal-to-noise ratio, we can follow these implementation steps: First, select an appropriate Gaussian channel model for simulation experiments using MATLAB's communication toolbox functions such as awgn (Additive White Gaussian Noise) for noise addition. Then, for different SNR values ranging typically from 0 to 20 dB, generate random binary data, modulate it using schemes like BPSK, pass it through the Gaussian channel, and demodulate the received signal. The key algorithm involves calculating the bit error rate by comparing transmitted and received bits using MATLAB's biterr function. Finally, plot the BER versus SNR curve using semilogy to visualize the logarithmic relationship. This experimental data helps us better understand the BER-SNR relationship and predict system performance under various SNR conditions. Such simulation and analysis are crucial for communication system design and optimization, particularly for evaluating modulation scheme performance and channel coding effectiveness.