Semi-blind Iterative Joint Channel Estimation and K-Best Sphere Decoding for MIMO

被引：0
|
作者：
Dey, I. [1 ]
Messier, G. G. [1 ]
Magierowski, S. [1 ]
Chen, Sheng [2 ]
机构：
[1] Univ Calgary, Sch Elect & Comp Engn, Calgary, AB, Canada
[2] Univ Southampton, Fac Phys & Appl Sci, Elect & Comp Sci, Southampton, Hants, England
来源：
2013 IEEE PACIFIC RIM CONFERENCE ON COMMUNICATIONS, COMPUTERS AND SIGNAL PROCESSING (PACRIM) | 2013年
关键词：
Multiple-input multiple-output; K-Best Sphere Decoding; joint channel estimation and data detection;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
An efficient and high-performance semi-blind scheme is proposed for Multiple-Input Multiple-Output (MIMO) systems by iteratively combining channel estimation with K-Best Sphere Decoding (SD). To avoid the exponentially increasing complexity of Maximum Likelihood Detection (MLD) while achieving a near optimal MLD performance, K-best SD is considered to accomplish data detection. Semi-blind iterative estimation is adopted for identifying the MIMO channel matrix. Specifically, a training-based least squares channel estimate is initially provided to the K-best SD data detector, and the channel estimator and the data detector then iteratively exchange information to perform the decision-directed channel update and consequently to enhance the detection performance. The proposed scheme is capable of approaching the ideal detection performance obtained with the perfect MIMO channel state information.
引用
收藏
页码：37 / 40
页数：4
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