Different Adaptive Beamforming Algorithms for Performance Investigation of Smart Antenna System

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationSoftCOM 2016 - 2016 24th INTERNATIONAL CONFERENCE ON SOFTWARE, TELECOMMUNICATIONS AND COMPUTER NETWORKS (SoftCOM)
EditorsNikola Rožić, Dinko Begušić, Matko Šarić
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Pages307-312
ISBN (print)978-1-5090-2578-7
Publication statusPublished - Sept 2016
Externally publishedYes

Publication series

Name
ISSN (electronic)1847-358X

Conference

Title24th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2016)
PlaceCroatia
CitySplit
Period22 - 24 September 2016

Link(s)

DOI

DOI
Check@CityULib
Link to Scopus https://www.scopus.com/record/display.uri?eid=2-s2.0-85010468580&origin=recordpage
Permanent Link https://scholars.cityu.edu.hk/en/publications/publication(77519e72-bdfb-4116-9417-efdcdf539cd0).html

Abstract

Smart antenna systems are of great importance in wireless communication and radar applications. They effectively enhance the system capacity and reduce the co-channel interference. Smart antenna is an array antenna that uses adaptive beamforming algorithms to steer the main beam toward the desired signal direction and reject the interfering signals of the same frequency from other directions without moving the antenna. This is achieved by continuously updating the weights of each radiating element (antenna). An algorithm with low complexity, low computation costs, high speed convergence rates and better performance is usually preferred. This paper introduces a new performance investigation and comparison between five different beamforming algorithms: Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Sample Matrix Inversion (SMI), Recursive Least Square (RLS) and Hybrid Least Mean Square / Sample Matrix Inversion (LMS/SMI). In this investigation, the number of array elements and the displacement among them are changed in each algorithm. Simulation experiments are carried out, and the results are compared to verify the effectiveness of this investigation. The performance of each algorithm is optimized and demonstrated using MATLAB software package.

Research Area(s)

  • smart antenna, adaptive beamforming, least mean square, sample matrix inversion, recursive least square

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Publication fingerprints text

100
Antenna System Engineering
100
Least Mean Square Engineering
100
Adaptive Beamformin... Engineering
100
smart antenna Computer Science
66
Antenna Engineering
66
Sample Matrix Engineering
66
Least-Mean-Square A... Computer Science
33
Recursive Engineering
33
Least Square Engineering
33
Simulation Experime... Engineering
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Citation Format(s)

[ RIS ] [ BibTeX ]
Different Adaptive Beamforming Algorithms for Performance Investigation of Smart Antenna System. / Khalaf, Ashraf A. M.; El-Daly, Abdel-Rahman B. M.; Hamed, Hesham F. A.
SoftCOM 2016 - 2016 24th INTERNATIONAL CONFERENCE ON SOFTWARE, TELECOMMUNICATIONS AND COMPUTER NETWORKS (SoftCOM). ed. / Nikola Rožić; Dinko Begušić; Matko Šarić. Institute of Electrical and Electronics Engineers, Inc., 2016. p. 307-312 7772134.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review