LS Algorithm Implementation in Broadband Adaptive Beamforming

This paper presents the MATLAB implementation of the Least Squares (LS) algorithm for broadband adaptive beamforming. Beamforming is a signal processing technique that enhances desired signals and suppresses interference by adjusting weight coefficients in antenna arrays. The LS algorithm, a widely used adaptive beamforming approach, minimizes the error between the output signal and the desired reference signal to optimize beam patterns. Our implementation involves MATLAB programming to demonstrate the algorithm's core functionality, including weight vector calculation through matrix operations and real-time adaptation mechanisms. Through simulation experiments, we validate the algorithm's performance in terms of interference suppression capability and beam steering accuracy. This work provides readers with comprehensive insights into the LS algorithm's theoretical foundations and practical implementation process, serving as a valuable reference for broadband adaptive beamforming research. Key MATLAB functions utilized include matrix inversion operations for optimal weight computation and spectral analysis tools for performance evaluation.