LS Algorithm Implementation for Rayleigh Fading Channel Analysis

This MATLAB implementation presents a Least Squares (LS) algorithm tailored for Rayleigh fading channel environments, offering valuable reference material and implementation guidance for communication system analysis. The program includes key components for channel modeling and parameter estimation: 1. Rayleigh fading channel generation using complex Gaussian random variables 2. Pilot signal insertion and transmission simulation 3. LS channel estimation implementation with matrix operations 4. Performance evaluation metrics calculation (MSE, BER) Key MATLAB functions employed: - randn() for generating Gaussian noise components - matrix inversion (inv() or pinv()) for LS solution computation - convolution operations for signal transmission simulation - plotting functions for visualization of channel estimates and error performance The algorithm demonstrates how to estimate channel coefficients by minimizing the squared error between received signals and known pilot sequences, providing a foundation for more advanced channel estimation techniques in wireless communication systems.