Paper Info
Title
Partial Perturbation to Alleviate the Performance Degradation of Vector Perturbation With Inaccurate Power Scaling Factors
Abstract
For multi-user multiple-input-multiple-output (MU-MIMO) system, transmitter utilizes a pre-equalizer based precoding to cancel inter-stream interference for parallel transmission with the aid of accurate feedback of channel state information (CSI) from all receivers. The correct power scaling factor, which normalizes the symbols power of precoding to be a constant one, is required at each receiver. Due to CSI error and limitation of feed-forward link, the received inaccurate power scaling factor will shrink or expand the received constellation points which severely degrades the performance of MIMO system. In this paper, using nonlinear vector perturbation (VP) and linear zero-forcing (ZF) precoding, we analyze the impact of inaccurate power scaling factor on the performance of a MIMO precoding system. The analyzed results show that the mismatched modulo size from inaccurate power scaling factor severely degrades the performance of the VP system, especially for high order M-QAM modulation. In addition, the performance degradation is strongly related with the distribution of representation points for each M-QAM symbol. For linear ZF precoding, the performance loss from the shrinked or expanded constellation points is severe for system using high order M-QAM. In addition, to alleviate the performance degradation, we propose a VP system using partial perturbation points (PPP). By limiting the region of redundant points with vector perturbation for partial M-QAM symbols, the performance degradation due to the inaccurate power scaling factor can be alleviated.
Year
DOI
Venue
2021
10.1109/TBC.2020.2977514
IEEE Transactions on Broadcasting
Keywords
DocType
Volume
MIMO,precoding,dirty paper coding,performance analysis,inaccurate power scaling factor,vector perturbation
Journal
67
Issue
ISSN
Citations 
1
0018-9316
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Yafei Hou11211.89
Satoshi Denno213.07