Robust multi-user detection based on hybrid grey wolf optimization
The search for an effective nature-inspired optimization technique has certainly continued for decades. In this paper, a novel hybrid Grey wolf optimization and differential evolution algorithm robust multi-user detection algorithm is proposed to overcome the problem of high bit error rate (BER) in...
| Main Authors: | , , , , , , , |
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| Format: | Book Chapter |
| Language: | English English English |
| Published: |
Springer Nature Switzerland
2020
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| Online Access: | http://umpir.ump.edu.my/id/eprint/25061/ http://umpir.ump.edu.my/id/eprint/25061/1/Robust%20multi-user%20detection%20based%20on%20hybrid%20grey%20wolf%20optimization.pdf http://umpir.ump.edu.my/id/eprint/25061/7/16.%20Robust%20Multi-user%20Detection%20Based%20on%20Hybrid%20Grey%20Wolf%20Optimization.pdf http://umpir.ump.edu.my/id/eprint/25061/8/16.1%20Robust%20Multi-user%20Detection%20Based%20on%20Hybrid%20Grey%20Wolf%20Optimization.pdf |
| _version_ | 1848822190503362560 |
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| author | Ji, Yuanfa Fan, Z . Sun, X. Wang, S. Yan, S. Wu, S. Fu, Q. Kamarul Hawari, Ghazali |
| author2 | Lu, Huimin |
| author_facet | Lu, Huimin Ji, Yuanfa Fan, Z . Sun, X. Wang, S. Yan, S. Wu, S. Fu, Q. Kamarul Hawari, Ghazali |
| author_sort | Ji, Yuanfa |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | The search for an effective nature-inspired optimization technique has certainly continued for decades. In this paper, a novel hybrid Grey wolf optimization and differential evolution algorithm robust multi-user detection algorithm is proposed to overcome the problem of high bit error rate (BER) in multi-user detection under impulse noise environment. The simulation results show that the iteration times of the multi-user detector based on the proposed algorithm is less than that of genetic algorithm, differential evolution algorithm and Grey wolf optimization algorithm, and has the lower BER. |
| first_indexed | 2025-11-15T02:37:18Z |
| format | Book Chapter |
| id | ump-25061 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English English |
| last_indexed | 2025-11-15T02:37:18Z |
| publishDate | 2020 |
| publisher | Springer Nature Switzerland |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-250612020-05-27T06:54:35Z http://umpir.ump.edu.my/id/eprint/25061/ Robust multi-user detection based on hybrid grey wolf optimization Ji, Yuanfa Fan, Z . Sun, X. Wang, S. Yan, S. Wu, S. Fu, Q. Kamarul Hawari, Ghazali QA Mathematics TK Electrical engineering. Electronics Nuclear engineering The search for an effective nature-inspired optimization technique has certainly continued for decades. In this paper, a novel hybrid Grey wolf optimization and differential evolution algorithm robust multi-user detection algorithm is proposed to overcome the problem of high bit error rate (BER) in multi-user detection under impulse noise environment. The simulation results show that the iteration times of the multi-user detector based on the proposed algorithm is less than that of genetic algorithm, differential evolution algorithm and Grey wolf optimization algorithm, and has the lower BER. Springer Nature Switzerland Lu, Huimin 2020 Book Chapter PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25061/1/Robust%20multi-user%20detection%20based%20on%20hybrid%20grey%20wolf%20optimization.pdf pdf en http://umpir.ump.edu.my/id/eprint/25061/7/16.%20Robust%20Multi-user%20Detection%20Based%20on%20Hybrid%20Grey%20Wolf%20Optimization.pdf pdf en http://umpir.ump.edu.my/id/eprint/25061/8/16.1%20Robust%20Multi-user%20Detection%20Based%20on%20Hybrid%20Grey%20Wolf%20Optimization.pdf Ji, Yuanfa and Fan, Z . and Sun, X. and Wang, S. and Yan, S. and Wu, S. and Fu, Q. and Kamarul Hawari, Ghazali (2020) Robust multi-user detection based on hybrid grey wolf optimization. In: Cognitive internet of things : frameworks, tools and aplications. Studies in Computational Intelligence, 810 (810). Springer Nature Switzerland, pp. 237-249. ISBN 978-3-030-04946-1 https://link.springer.com/chapter/10.1007/978-3-030-04946-1_23 DOI: https://doi.org/10.1007/978-3-030-04946-1_23 |
| spellingShingle | QA Mathematics TK Electrical engineering. Electronics Nuclear engineering Ji, Yuanfa Fan, Z . Sun, X. Wang, S. Yan, S. Wu, S. Fu, Q. Kamarul Hawari, Ghazali Robust multi-user detection based on hybrid grey wolf optimization |
| title | Robust multi-user detection based on hybrid grey wolf optimization |
| title_full | Robust multi-user detection based on hybrid grey wolf optimization |
| title_fullStr | Robust multi-user detection based on hybrid grey wolf optimization |
| title_full_unstemmed | Robust multi-user detection based on hybrid grey wolf optimization |
| title_short | Robust multi-user detection based on hybrid grey wolf optimization |
| title_sort | robust multi-user detection based on hybrid grey wolf optimization |
| topic | QA Mathematics TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/25061/ http://umpir.ump.edu.my/id/eprint/25061/ http://umpir.ump.edu.my/id/eprint/25061/ http://umpir.ump.edu.my/id/eprint/25061/1/Robust%20multi-user%20detection%20based%20on%20hybrid%20grey%20wolf%20optimization.pdf http://umpir.ump.edu.my/id/eprint/25061/7/16.%20Robust%20Multi-user%20Detection%20Based%20on%20Hybrid%20Grey%20Wolf%20Optimization.pdf http://umpir.ump.edu.my/id/eprint/25061/8/16.1%20Robust%20Multi-user%20Detection%20Based%20on%20Hybrid%20Grey%20Wolf%20Optimization.pdf |