Paper Info
Title
Joint Precoder, Reflection Coefficients, and Equalizer Design for IRS-Assisted MIMO Systems
Abstract
The incorporation of intelligent reflecting surface (IRS) into wireless communication systems can extend the coverage and enhance the data transmission rate. This paper studies the joint transceiver and IRS designs in IRS-assisted multi-input multi-output (MIMO) systems under both perfect channel state information (CSI) and imperfect CSI. Specifically, the transmit precoder, reflection coefficients at the IRS, and receive equalizer are jointly optimized to minimize the data detection mean square error (MSE), subject to the transmission power constraint and the modulus constraints for IRS reflection coefficients. The design problems, non-convex and challenging, are tackled under the framework of alternating optimization. For the design with perfect CSI, we successively optimize the IRS reflection coefficients given the precoder and present the closed-form optimal angle of one reflection coefficient given the others. For the robust design with imperfect CSI, we first average the detection MSE over channel uncertainties by using a generalized statistical CSI error model. Then, the averaged MSE is approximated by a more tractable upper bound. Subsequently, the robust design problem is elaborately transformed into a form similar to the problem with perfect CSI. Numerical results demonstrate the effectiveness of the proposed designs as compared to various benchmark schemes.
Year
DOI
Venue
2022
10.1109/TCOMM.2022.3168284
IEEE Transactions on Communications
Keywords
DocType
Volume
Intelligent reflecting surface (IRS),multi-input multi-output (MIMO),robust design,channel state information (CSI)
Journal
70
Issue
ISSN
Citations 
6
0090-6778
0
PageRank 
References 
Authors
0.34
35
5
Name
Order
Citations
PageRank
Wen Zhou110.69
Junjuan Xia210313.55
Chunguo Li34810.72
Lisheng Fan475950.06
Arumugam Nallanathan53694237.64