NDLI: Near-optimal MIMO multiuser detection using hybrid immune clonal selection algorithm

Content Provider	IEEE Xplore Digital Library
Author	Aihua Wang Binbin Xu Ronghua Zhou Zhongxia He
Copyright Year	2008
Description	Author affiliation: Commun. & Network Lab., Beijing Inst. of Technol., Beijing (Aihua Wang; Binbin Xu; Ronghua Zhou; Zhongxia He)
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.
Starting Page	983
Ending Page	986
File Size	1193479
Page Count	4
File Format	PDF
ISBN	9781424423736
DOI	10.1109/CHINACOM.2008.4685189
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multiuser detection Maximum likelihood detection Transmitting antennas Receiving antennas Transfer functions Detectors Interference MIMO Communications technology Equations
Content Type	Text
Resource Type	Article

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