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Performance Comparison in Digital Beamforming Using LMS, RLS and D3LS Algorithms

Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.5, No. 5)

Publication Date:

Authors : ; ;

Page : 221-230

Keywords : Direct Data Domain Least Square; Recursive Least Square; Least Mean Square; Digital Beamforming; Complex Weights; Windowing Functions;

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Abstract

This paper presents a performance comparison of three different adaptive algorithms used in digital beamforming. These algorithms are used for the autonomous motion of the beams and for the cancellation of interferences. Discussion of using the least mean square, recursive least square and direct data domain least square algorithms for controlling the beam width, directivity, and sidelobe level are presented. The simulation results indicate that for least mean square and recursive mean square algorithms, the sidelobe level of the beam pattern remains the same for any number of antenna elements. The direct data domain least square algorithm enables us to achieve different sidelobes for same number of antenna elements. Based on the simulation results, an effective algorithm can be chosen to be used in a beamforming network according to the application. Direct data domain least square algorithm requires less time to determine the weights for digital beamforming compared to recursive least mean square algorithms which is has faster processing when compared to least mean square algorithm.

Last modified: 2016-05-17 02:27:30