标题: Robust MIMO Detection Under Imperfect CSI Based on Bayesian Model Selection
作者: Cheng, Chien-Chun
Sezginer, Serdar
Sari, Hikmet
Su, Yu T.
电子工程学系及电子研究所
Department of Electronics Engineering and Institute of Electronics
关键字: Channel estimation;ML detection;OFDM;MIMO
公开日期: 八月-2013
摘要: A robust receiver for multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems is proposed. We are interested in the scenario when only a limited number of observations in both time and frequency domains are available. For this scenario, perfect channel state information is impossible to obtain and the receiver suffers from statistical information mismatch. To overcome this limitation, we first propose the optimum receiver by performing jointly channel and data estimation. For statistical information mismatch, we construct a finite set of covariance matrices and derive a model-selection scheme based on Bayesian Model Selection. Finally, the sliding-window scheme is used in order to enhance the model selection accuracy. Simulation results are presented, showing that the proposed scheme outperforms the conventional scheme under imperfect channel knowledge.
URI: http://dx.doi.org/10.1109/WCL.2013.042313.130148
http://hdl.handle.net/11536/133692
ISSN: 2162-2337
DOI: 10.1109/WCL.2013.042313.130148
期刊: IEEE WIRELESS COMMUNICATIONS LETTERS
Volume: 2
Issue: 4
起始页: 375
结束页: 378
显示于类别:Articles