QAM Communication System Simulation with Time Domain Equalization

This document presents a comprehensive simulation of a QAM communication system incorporating time-domain equalization, followed by statistical analysis of bit error rates. The implementation typically involves MATLAB or Simulink modeling with digital signal processing components. We begin by explaining the fundamental principles and operational mechanisms of QAM communication systems, including constellation mapping and demodulation algorithms. Subsequently, we detail the design and implementation of time-domain equalizers using adaptive filtering algorithms like LMS (Least Mean Squares) or RLS (Recursive Least Squares) to mitigate channel distortions and improve system performance. The simulation leverages communication toolbox functions for generating QAM signals, adding channel impairments, and applying equalization filters. Through systematic experiments using Monte Carlo simulations, we evaluate system performance under varying SNR conditions. Finally, we employ statistical processing functions to calculate and visualize bit error rates, providing crucial insights into system reliability and performance characteristics through BER vs. SNR curves and error distribution analysis.