PSOGSA-explore: a new hybrid metaheuristic approach for beampattern optimization in collaborative beamforming
A conventional collaborative beamforming (CB) system suffers from high sidelobes due to the random positioning of the nodes. This paper introduces a hybrid metaheuristic optimization algorithm called the Particle Swarm Optimization and Gravitational Search Algorithm-Explore (PSOGSA-E) to suppress th...
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| Format: | Article |
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Elsevier BV
2015
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| _version_ | 1796860086445932544 |
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| author | Jayaprakasam, Suhanya Abdul Rahim, Sharul Kamal Leow, Cheeyen |
| author_facet | Jayaprakasam, Suhanya Abdul Rahim, Sharul Kamal Leow, Cheeyen |
| author_sort | Jayaprakasam, Suhanya |
| collection | ePrints |
| description | A conventional collaborative beamforming (CB) system suffers from high sidelobes due to the random positioning of the nodes. This paper introduces a hybrid metaheuristic optimization algorithm called the Particle Swarm Optimization and Gravitational Search Algorithm-Explore (PSOGSA-E) to suppress the peak sidelobe level (PSL) in CB, by the means of finding the best weight for each node. The proposed algorithm combines the local search ability of the gravitational search algorithm (GSA) with the social thinking skills of the legacy particle swarm optimization (PSO) and allows exploration to avoid premature convergence. The proposed algorithm also simplifies the cost of variable parameter tuning compared to the legacy optimization algorithms. Simulations show that the proposed PSOGSA-E outperforms the conventional, the legacy PSO, GSA and PSOGSA optimized collaborative beamformer by obtaining better results faster, producing up to 100% improvement in PSL reduction when the disk size is small. |
| first_indexed | 2024-03-05T19:36:43Z |
| format | Article |
| id | utm.eprints-55114 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:36:43Z |
| publishDate | 2015 |
| publisher | Elsevier BV |
| record_format | dspace |
| spelling | utm.eprints-551142016-08-24T06:46:02Z http://eprints.utm.my/55114/ PSOGSA-explore: a new hybrid metaheuristic approach for beampattern optimization in collaborative beamforming Jayaprakasam, Suhanya Abdul Rahim, Sharul Kamal Leow, Cheeyen TK Electrical engineering. Electronics Nuclear engineering A conventional collaborative beamforming (CB) system suffers from high sidelobes due to the random positioning of the nodes. This paper introduces a hybrid metaheuristic optimization algorithm called the Particle Swarm Optimization and Gravitational Search Algorithm-Explore (PSOGSA-E) to suppress the peak sidelobe level (PSL) in CB, by the means of finding the best weight for each node. The proposed algorithm combines the local search ability of the gravitational search algorithm (GSA) with the social thinking skills of the legacy particle swarm optimization (PSO) and allows exploration to avoid premature convergence. The proposed algorithm also simplifies the cost of variable parameter tuning compared to the legacy optimization algorithms. Simulations show that the proposed PSOGSA-E outperforms the conventional, the legacy PSO, GSA and PSOGSA optimized collaborative beamformer by obtaining better results faster, producing up to 100% improvement in PSL reduction when the disk size is small. Elsevier BV 2015-05 Article PeerReviewed Jayaprakasam, Suhanya and Abdul Rahim, Sharul Kamal and Leow, Cheeyen (2015) PSOGSA-explore: a new hybrid metaheuristic approach for beampattern optimization in collaborative beamforming. Applied Soft Computing Journal, 30 . pp. 229-237. ISSN 1568-4946 http://dx.doi.org/10.1016/j.asoc.2015.01.024 DOI:10.1016/j.asoc.2015.01.024 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Jayaprakasam, Suhanya Abdul Rahim, Sharul Kamal Leow, Cheeyen PSOGSA-explore: a new hybrid metaheuristic approach for beampattern optimization in collaborative beamforming |
| title | PSOGSA-explore: a new hybrid metaheuristic approach for beampattern optimization in collaborative beamforming |
| title_full | PSOGSA-explore: a new hybrid metaheuristic approach for beampattern optimization in collaborative beamforming |
| title_fullStr | PSOGSA-explore: a new hybrid metaheuristic approach for beampattern optimization in collaborative beamforming |
| title_full_unstemmed | PSOGSA-explore: a new hybrid metaheuristic approach for beampattern optimization in collaborative beamforming |
| title_short | PSOGSA-explore: a new hybrid metaheuristic approach for beampattern optimization in collaborative beamforming |
| title_sort | psogsa explore a new hybrid metaheuristic approach for beampattern optimization in collaborative beamforming |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
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