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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| Other Authors: | |
| Format: | Book Section |
| Language: | English |
| Published: |
Springer International Publishing
2020
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| Subjects: | |
| Online Access: | 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 |
| Summary: | 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. |
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