PERFORMANCE IMPROVEMENT FOR SMART ANTENNA SYSTEM LEAST SQUARE BEAMFORMING ALGORITHMS

Abstract

Smart antenna is great prominence in many applications like radar and wireless communication. The adaptive algorithms are periodically updated the weight vector to monitor the desired signal sources in a time-varying environment by modifying the array pattern with nulls to the direction of the sources of interference. A major goal of this paper is to simulate different improvement aspect of conventional adaptive algorithms that has step size factor (μ) for spatial beamforming and normalizing the least square algorithm by SIR factor, here, simulations are carried out using a MATLAB system to adjust the weight value for better performance and computational complexity and to compare the characteristics of the algorithms. Also in this paper presents the comparison for the effeteness of two array geometry by calculating the BER factor for both and also the relation between the number of antenna for them and SNR factor. Regularly to defeat the computational complexity problem this paper would introduce a new investigation of achievements and a study of two enhanced beamforming algorithms: Least Mean Square Step Size Improvements (LMSSI) and Normalized Least Mean Square by signal to interference ratio improved (SIR-LMS), both algorithm are comparable in convergence rate. The LMSSI has a slower rate of convergence than the SIR-LMS, but much faster than a standard LMS algorithm.