Abstract
We propose in this paper an hybrid immune clonal selection algorithm (ICSA) to approach near-optimal performance for multiple-input multiple-output (MIMO) multiuser detection. The ICSA which guide the heuristic search by imitating the evolutionary mechanism of antibodies, is shown to approach the performance of maximum-likelihood (ML) detector. The Hybrid ICSA multiuser detection (MUD) approach, which introduce embedded Hopfield neural networks (HNN) to accelerate the search convergence and improve local search capability, is further proposed. The simulation results show that it is feasible to achieve near-optimal bit-error-rate (BER) performance with a lower complexity using the proposed algorithm.
| Original language | English |
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| Title of host publication | 3rd International Conference on Communications and Networking in China, ChinaCom 2008 |
| Pages | 983-986 |
| Number of pages | 4 |
| DOIs | |
| Publication status | Published - 2008 |
| Event | 3rd International Conference on Communications and Networking in China, ChinaCom 2008 - Hangzhou, China Duration: 25 Aug 2008 → 27 Aug 2008 |
Publication series
| Name | 3rd International Conference on Communications and Networking in China, ChinaCom 2008 |
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Conference
| Conference | 3rd International Conference on Communications and Networking in China, ChinaCom 2008 |
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| Country/Territory | China |
| City | Hangzhou |
| Period | 25/08/08 → 27/08/08 |
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Wang, A., Xu, B., Zhou, R., & He, Z. (2008). Near-optimal MIMO multiuser detection using hybrid immune clonal selection algorithm. In 3rd International Conference on Communications and Networking in China, ChinaCom 2008 (pp. 983-986). Article 4685189 (3rd International Conference on Communications and Networking in China, ChinaCom 2008). https://doi.org/10.1109/CHINACOM.2008.4685189