DocumentCode :
110520
Title :
Linear Precoding for the MIMO Multiple Access Channel With Finite Alphabet Inputs and Statistical CSI
Author :
Yongpeng Wu ; Chao-Kai Wen ; Chengshan Xiao ; Xiqi Gao ; Schober, Robert
Author_Institution :
Nat. Mobile Commun. Res. Lab., Southeast Univ., Nanjing, China
Volume :
14
Issue :
2
fYear :
2015
fDate :
Feb. 2015
Firstpage :
983
Lastpage :
997
Abstract :
In this paper, we investigate the design of linear precoders for the multiple-input-multiple-output (MIMO) multiple access channel (MAC). We assume that statistical channel state information (CSI) is available at the transmitters and consider the problem under the practical finite alphabet input assumption. First, we derive an asymptotic (in the large system limit) expression for the weighted sum rate (WSR) of the MIMO MAC with finite alphabet inputs and Weichselberger´s MIMO channel model. Subsequently, we obtain the optimal structures of the linear precoders of the users maximizing the asymptotic WSR and an iterative algorithm for determining the precoders. We show that the complexity of the proposed precoder design is significantly lower than that of MIMO MAC precoders designed for finite alphabet inputs and instantaneous CSI. Simulation results for finite alphabet signaling indicate that the proposed precoder achieves significant performance gains over existing precoder designs.
Keywords :
MIMO communication; linear codes; precoding; radio transmitters; statistical analysis; wireless channels; WSR; Weichselberger MIMO multiple access channel model; finite alphabet input assumption; finite alphabet signaling input; iterative algorithm; linear precoding; multiple-input-multiple-output MAC; statistical CSI; statistical channel state information; transmitter; weighted sum rate; Channel models; Fading; Iterative methods; MIMO; Mutual information; Transmitters; Vectors; Finite alphabet; MIMO MAC; linear precoding; statistical CSI;
fLanguage :
English
Journal_Title :
Wireless Communications, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-1276
Type :
jour
DOI :
10.1109/TWC.2014.2363105
Filename :
6924792
Link To Document :
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