Revisiting smart antenna array design with multiple interferers using basic adaptive beamforming algorithms: Comparative performance study with testbed results

Abstract Smart antennas are becoming popular in the area of cellular wireless communication for capacity enhancement and reduction of the multipath effect and interference. The demand for smart antennas is widely increasing as 5G cellular communication evolves to support the higher data rate and ban...

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Main Authors: SK Imtiaj, Iti Saha Misra, Sandipan Bhattacharya
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Engineering Reports
Subjects:
LMS
Online Access:https://doi.org/10.1002/eng2.12295
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spelling doaj-885bc9fccecf458ba2f8ab61f0790ce12021-03-23T16:20:06ZengWileyEngineering Reports2577-81962021-01-0131n/an/a10.1002/eng2.12295Revisiting smart antenna array design with multiple interferers using basic adaptive beamforming algorithms: Comparative performance study with testbed resultsSK Imtiaj0Iti Saha Misra1Sandipan Bhattacharya2ETCE Department Jadavpur University Kolkata IndiaETCE Department Jadavpur University Kolkata IndiaETCE Department Jadavpur University Kolkata IndiaAbstract Smart antennas are becoming popular in the area of cellular wireless communication for capacity enhancement and reduction of the multipath effect and interference. The demand for smart antennas is widely increasing as 5G cellular communication evolves to support the higher data rate and bandwidth. The basic principle of smart antenna design is adaptive beamforming using the best suited digital signal processing algorithms, such as least mean square (LMS), normalized least mean square (NLMS), sample matrix inversion (SMI), and recursive least square (RLS), each having its pros and cons. Among these, the LMS and NLMS are iterative approaches while SMI is a block adaptive method and RLS is a recursive method. The contribution of this article includes easy implementation of four adaptive beamforming algorithms, namely LMS, NLMS, SMI, and RLS. Furthermore, an exhaustive comparative performance analysis is carried out under five interferers and evaluated in terms of beamwidth, null depth, maximum sidelobe level, rate of convergence, error variation for the number of antenna elements, and spacing. Finally, a contrast table is presented to demonstrate the pros and cons of the listed algorithms. Time and dynamic space complexity are studied for RLS and SMI beamforming algorithms. Performance results from a designed reconfigurable testbed model for weight adaptation and smart beamforming are also presented for analysis and a better understanding of the real implementation of the smart algorithms through testbed design. The simulation and testbed results create the ground work for future exploration in the design of smart antenna beamforming.https://doi.org/10.1002/eng2.12295adaptive beamformingcomparative studycomplexity analysisLMSmultiple interferersNLMS
collection DOAJ
language English
format Article
sources DOAJ
author SK Imtiaj
Iti Saha Misra
Sandipan Bhattacharya
spellingShingle SK Imtiaj
Iti Saha Misra
Sandipan Bhattacharya
Revisiting smart antenna array design with multiple interferers using basic adaptive beamforming algorithms: Comparative performance study with testbed results
Engineering Reports
adaptive beamforming
comparative study
complexity analysis
LMS
multiple interferers
NLMS
author_facet SK Imtiaj
Iti Saha Misra
Sandipan Bhattacharya
author_sort SK Imtiaj
title Revisiting smart antenna array design with multiple interferers using basic adaptive beamforming algorithms: Comparative performance study with testbed results
title_short Revisiting smart antenna array design with multiple interferers using basic adaptive beamforming algorithms: Comparative performance study with testbed results
title_full Revisiting smart antenna array design with multiple interferers using basic adaptive beamforming algorithms: Comparative performance study with testbed results
title_fullStr Revisiting smart antenna array design with multiple interferers using basic adaptive beamforming algorithms: Comparative performance study with testbed results
title_full_unstemmed Revisiting smart antenna array design with multiple interferers using basic adaptive beamforming algorithms: Comparative performance study with testbed results
title_sort revisiting smart antenna array design with multiple interferers using basic adaptive beamforming algorithms: comparative performance study with testbed results
publisher Wiley
series Engineering Reports
issn 2577-8196
publishDate 2021-01-01
description Abstract Smart antennas are becoming popular in the area of cellular wireless communication for capacity enhancement and reduction of the multipath effect and interference. The demand for smart antennas is widely increasing as 5G cellular communication evolves to support the higher data rate and bandwidth. The basic principle of smart antenna design is adaptive beamforming using the best suited digital signal processing algorithms, such as least mean square (LMS), normalized least mean square (NLMS), sample matrix inversion (SMI), and recursive least square (RLS), each having its pros and cons. Among these, the LMS and NLMS are iterative approaches while SMI is a block adaptive method and RLS is a recursive method. The contribution of this article includes easy implementation of four adaptive beamforming algorithms, namely LMS, NLMS, SMI, and RLS. Furthermore, an exhaustive comparative performance analysis is carried out under five interferers and evaluated in terms of beamwidth, null depth, maximum sidelobe level, rate of convergence, error variation for the number of antenna elements, and spacing. Finally, a contrast table is presented to demonstrate the pros and cons of the listed algorithms. Time and dynamic space complexity are studied for RLS and SMI beamforming algorithms. Performance results from a designed reconfigurable testbed model for weight adaptation and smart beamforming are also presented for analysis and a better understanding of the real implementation of the smart algorithms through testbed design. The simulation and testbed results create the ground work for future exploration in the design of smart antenna beamforming.
topic adaptive beamforming
comparative study
complexity analysis
LMS
multiple interferers
NLMS
url https://doi.org/10.1002/eng2.12295
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AT itisahamisra revisitingsmartantennaarraydesignwithmultipleinterferersusingbasicadaptivebeamformingalgorithmscomparativeperformancestudywithtestbedresults
AT sandipanbhattacharya revisitingsmartantennaarraydesignwithmultipleinterferersusingbasicadaptivebeamformingalgorithmscomparativeperformancestudywithtestbedresults
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