Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals

Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals

Background/Objectives: Minimum Variance Distortionless Response (MVDR) beam forming technique is among the most widely used in antenna array field. The conventional MVDR has poor performance, and low Signal to Interference plus Noise Ratio (SINR) gain in the condition of limited snapshots or Multipl...

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Main Authors: Suhail Najm, Shahab, Ayib Rosdi, Zainun, Nurul Hazlina, Noordin, Izzeldin, I. Mohd
Format: Article
Language:English
Published: Informatics Publishing Limited 2018
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/20609/
http://umpir.ump.edu.my/id/eprint/20609/
http://umpir.ump.edu.my/id/eprint/20609/
http://umpir.ump.edu.my/id/eprint/20609/1/Performance%20Comparison%20of%20Nature-inspired%20Optimization%20Algorithms%20Applied%20to%20MVDR%20Technique%20for%20Canceling%20Multiple%20Access%20Interference%20Signals.pdf
id ump-20609
recordtype eprints
spelling ump-206092018-02-23T03:42:08Z http://umpir.ump.edu.my/id/eprint/20609/ Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals Suhail Najm, Shahab Ayib Rosdi, Zainun Nurul Hazlina, Noordin Izzeldin, I. Mohd TK Electrical engineering. Electronics Nuclear engineering Background/Objectives: Minimum Variance Distortionless Response (MVDR) beam forming technique is among the most widely used in antenna array field. The conventional MVDR has poor performance, and low Signal to Interference plus Noise Ratio (SINR) gain in the condition of limited snapshots or Multiple Access Interference (MAI) signals existing. Heuristic optimization algorithms are broadly used to solve many engineering problems. Methods/Analysis: In this work, two nature-inspired optimization methods, namely Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) are applied to enhancing the conventional MVDR performance. In particular, the complex weight coefficients of the conventional MVDR solution are improved using both approaches. First, SINR calculated from MVDR basing linear antenna array configuration then the PSO and GSA implemented to minimizes the power of noise and interference in the constraint condition. The performance of the proposed methods is assessed based on various QoS criteria such as beampattern accuracy for azimuth and elevation scanning angles and SINR output. Findings: In comparison to conventional MVDR, the proposed algorithms have indicated that MVDRGSA providesfavorable agreement of synthesizing a maximum gain toward the desired real user angle while introducing deep null-forming in the undesired user directions. As a result, average SINR is evaluated over 20 runs in all simulation scenarios, the performance of MVDRGSA is better than the performance of MVDRPSO. Moreover, a good control over the null-forming level can be achieved by MVDRGSA for iteration number < 100 whereas MVDRPSO is simple and easy to implement but required more convergence time to get high SINR. Application/Improvements: In general, it was observed that MVDRGSA out performs the MVDRPSO with respect to solution quality, stability and convergence speed. Informatics Publishing Limited 2018 Article PeerReviewed application/pdf en cc_by http://umpir.ump.edu.my/id/eprint/20609/1/Performance%20Comparison%20of%20Nature-inspired%20Optimization%20Algorithms%20Applied%20to%20MVDR%20Technique%20for%20Canceling%20Multiple%20Access%20Interference%20Signals.pdf Suhail Najm, Shahab and Ayib Rosdi, Zainun and Nurul Hazlina, Noordin and Izzeldin, I. Mohd (2018) Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals. Indian Journal of Science and Technology, 11 (3). pp. 1-20. ISSN 0974-6846 (Print); 0974-5645 (Online) http://www.indjst.org/index.php/indjst/article/view/92398 DOI: 10.17485/ijst/2018/v11i3/92398
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Suhail Najm, Shahab
Ayib Rosdi, Zainun
Nurul Hazlina, Noordin
Izzeldin, I. Mohd
Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals
description Background/Objectives: Minimum Variance Distortionless Response (MVDR) beam forming technique is among the most widely used in antenna array field. The conventional MVDR has poor performance, and low Signal to Interference plus Noise Ratio (SINR) gain in the condition of limited snapshots or Multiple Access Interference (MAI) signals existing. Heuristic optimization algorithms are broadly used to solve many engineering problems. Methods/Analysis: In this work, two nature-inspired optimization methods, namely Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) are applied to enhancing the conventional MVDR performance. In particular, the complex weight coefficients of the conventional MVDR solution are improved using both approaches. First, SINR calculated from MVDR basing linear antenna array configuration then the PSO and GSA implemented to minimizes the power of noise and interference in the constraint condition. The performance of the proposed methods is assessed based on various QoS criteria such as beampattern accuracy for azimuth and elevation scanning angles and SINR output. Findings: In comparison to conventional MVDR, the proposed algorithms have indicated that MVDRGSA providesfavorable agreement of synthesizing a maximum gain toward the desired real user angle while introducing deep null-forming in the undesired user directions. As a result, average SINR is evaluated over 20 runs in all simulation scenarios, the performance of MVDRGSA is better than the performance of MVDRPSO. Moreover, a good control over the null-forming level can be achieved by MVDRGSA for iteration number < 100 whereas MVDRPSO is simple and easy to implement but required more convergence time to get high SINR. Application/Improvements: In general, it was observed that MVDRGSA out performs the MVDRPSO with respect to solution quality, stability and convergence speed.
format Article
author Suhail Najm, Shahab
Ayib Rosdi, Zainun
Nurul Hazlina, Noordin
Izzeldin, I. Mohd
author_facet Suhail Najm, Shahab
Ayib Rosdi, Zainun
Nurul Hazlina, Noordin
Izzeldin, I. Mohd
author_sort Suhail Najm, Shahab
title Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals
title_short Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals
title_full Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals
title_fullStr Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals
title_full_unstemmed Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals
title_sort performance comparison of nature-inspired optimization algorithms applied to mvdr technique for canceling multiple access interference signals
publisher Informatics Publishing Limited
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/20609/
http://umpir.ump.edu.my/id/eprint/20609/
http://umpir.ump.edu.my/id/eprint/20609/
http://umpir.ump.edu.my/id/eprint/20609/1/Performance%20Comparison%20of%20Nature-inspired%20Optimization%20Algorithms%20Applied%20to%20MVDR%20Technique%20for%20Canceling%20Multiple%20Access%20Interference%20Signals.pdf
first_indexed 2023-09-18T22:29:49Z
last_indexed 2023-09-18T22:29:49Z
_version_ 1777416210827182080

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