Comparative Study of Adaptive Beamforming Algorithms for Smart antenna Applications

Mohammad Abualhayja’a, Mousa Hussein

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Citations (Scopus)

Abstract

Beamforming is signal processing techniques used to shape the antenna array pattern according to prescribed criteria. In this paper, a comparative study is presented for various adaptive antenna beamforming algorithms. Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Recursive Least Square (RLS) and Sample Matrix Inversion (SMI) algorithms are studied and analyzed. we also consider some possible adaptive filters combinations, such as LMS with SMI weights initialization, and combined NLMS filters with a variable mixing parameter. These algorithms are simulated for a linear antenna array with different sizes, and results are discussed in terms of their Convergence speed, Max SLL and Null depths.

Original languageEnglish
Title of host publicationICCSPA 2020 - 4th International Conference on Communications, Signal Processing, and their Applications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728165356
DOIs
Publication statusPublished - Mar 16 2021
Event4th International Conference on Communications, Signal Processing, and their Applications, ICCSPA 2020 - Sharjah, United Arab Emirates
Duration: Mar 16 2021Mar 18 2021

Publication series

NameICCSPA 2020 - 4th International Conference on Communications, Signal Processing, and their Applications
Volume2021-January

Conference

Conference4th International Conference on Communications, Signal Processing, and their Applications, ICCSPA 2020
Country/TerritoryUnited Arab Emirates
CitySharjah
Period3/16/213/18/21

Keywords

  • Adaptive beamforming
  • LMS algorithm
  • NLMS algorithm
  • RLS algorithm
  • SMI algorithm

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications
  • Computer Science Applications

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