Title: Reduced-complexity maximum-likelihood decoding for 3D MIMO code

Speaker: Dr. Ming Liu

Time: 2:00pm, April 15, 2013, Monday

Venue: 信息学院四楼报告厅

 

Abstract: The 3D MIMO code is a robust and efficient space-time coding scheme for the distributed MIMO broadcasting. However, it suffers from the high decoding complexity if the optimal maximum-likelihood (ML) decoder is used. In this work, we first investigate the unique properties of the 3D MIMO code and consequently propose a simplified decoding algorithm without sacrificing the ML optimality. Analysis shows that the decoding complexity is reduced from O(M⁸) to O(M^4.5) in quasi-static channels when M-ary square QAM constellation is used. Moreover, we propose an efficient implementation of the simplified ML decoder which achieves a much lower decoding time delay compared to the classical sphere decoder with Schnorr-Euchner enumeration.

 

Biography: Ming Liu received the B.Eng. and M.Eng. degrees from the Xi'an Jiaotong University, China, in 2004 and 2007, respectively, and the Ph.D. degree from the National Institute of Applied Sciences (INSA), Rennes, France, in 2011, all in electrical engineering. He is with the Institute of Electronics and Telecommunications of Rennes (IETR) as a postdoctoral researcher. His main research interests include channel estimation and synchronization techniques for multicarrier transmissions, multiple-input multiple-output (MIMO) transmission, space-time coding and Turbo receiver.