Research on adaptive beamforming algorithm

Adaptive beamforming is a key technology of smart antenna; the core is to obtain the optimum weights of the antenna array by some adaptive beamforming algorithms, and finally adjust the main lobe to focus on the arriving direction of the desired signal, as well as suppress the interfering signal. By these ways, the antenna can receive the interesting signal efficiently. In practical application, the speed of convergence, complexity, and robustness are the main factors to be considered when choosing an adaptive beamforming algorithm. This paper focuses on the Least Mean Squares (LMS) algorithm and the Sample Matrix Inversion (SMI) algorithm, analyzes their performance and applies these two algorithms to adaptive beamforming with the help of Matlab.