Pilot pattern optimization for sparse channel estimation in OFDM systems

Wang, Han, Guo, Qing, Zhang, Gengxin, Li, Guangxia, and Xiang, Wei (2015) Pilot pattern optimization for sparse channel estimation in OFDM systems. IEEE Communications Letters, 19 (7). pp. 1233-1236.

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Compressive sensing (CS) based sparse channel estimation requires optimal pilot patterns, whose corresponding sensing matrices should have small mutual coherences, so as to efficiently exploit the inherent channel sparsity. For the purpose of minimizing the mutual coherence of the sensing matrix, we introduce a new estimation of distribution algorithm (EDA) to optimize the pilot pattern so as to improve the channel estimation performance. The proposed scheme guides the optimization process by building and sampling the probability distribution model of the promising pilot indexes, and approaches the optimal pilot pattern iteratively. The algorithm is able to not only preserve the current best pilot indexes, but also introduce diversity by sampling new ones, and hence is unlikely to trap into local minima and more robust than other methods. Simulation results show that our proposed method can generate sensing matrices with smaller mutual coherences than existing methods, and the corresponding optimized pilot pattern performs well in terms of sparse channel estimation.

Item ID: 42844
Item Type: Article (Research - C1)
ISSN: 1558-2558
Keywords: compressive sensing (CS), estimation of distribution algorithm (EDA), pilot pattern optimization, sparse channel estimation
Date Deposited: 18 Feb 2016 01:50
FoR Codes: 10 TECHNOLOGY > 1005 Communications Technologies > 100510 Wireless Communications @ 100%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8901 Communication Networks and Services > 890103 Mobile Data Networks and Services @ 100%
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