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Joint Transceiver Optimization for IRS-Aided MIMO Communications
Zhao, Xin1; Xu, Kaizhe2; Ma, Shaodan2; Gong, Shiqi2; Yang, Guanghua3; Xing, Chengwen4
2022-03-21
Source PublicationIEEE Transactions on Communications
ISSN0090-6778
Abstract

Intelligent reflecting surface (IRS) is an emerging cost-efficient technology to enhance communication performance by implementing a large number of passive reflecting elements with tunable phases in wireless systems. In this paper, we propose a general framework for the IRS-aided MIMO system designs under both single-user and multi-user setups, in which the diverse performance metrics including weighted mutual information and weighted MSE, and the realistic multiple weighted power constraint are taken into consideration. Leveraging the alternating optimization approach, the optimal IRS phase shifts are obtained in semi-closed forms. Specifically, based on the matrix-monotonic optimization theory, it is found that optimizing IRS phase shifts is essentially equivalent to tuning the eigenvalues and the corresponding eigenvectors of the MSE matrix. Then the proposed general framework is extended to a multi-user system by introducing a majorization-minimization (MM)-based method for IRS phase shift optimization. Simulation results show that our proposed optimal design brings significant enhancement on the chosen performance metric compared to the traditional MIMO systems without the IRS, and also significantly outperforms various benchmark designs in both single-user and multi-user systems.

KeywordArray Signal Processing Eigenvalue Decomposition General Performance Metrics Intelligent Reflecting Surface Matrix-monotonic Optimization Measurement Mimo Communication Mse Matrix Multi-user Mimo System Mutual Information Optimization Signal To Noise Ratio Transceivers
DOI10.1109/TCOMM.2022.3158954
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaEngineering ; Telecommunications
WOS SubjectEngineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000797439600044
Scopus ID2-s2.0-85127071355
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Document TypeJournal article
CollectionFaculty of Science and Technology
Corresponding AuthorMa, Shaodan
Affiliation1.School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China, and the Department of Electrical and Computer Engineering, University of Macau, Macau SAR 999078, China.
2.State Key Laboratory of Internet of Things for Smart City and the Department of Electrical and Computer Engineering, University of Macau, Macao SAR 999078, China.
3.Institute of Physical Internet and the School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai 519070, China.
4.School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China.
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Zhao, Xin,Xu, Kaizhe,Ma, Shaodan,et al. Joint Transceiver Optimization for IRS-Aided MIMO Communications[J]. IEEE Transactions on Communications,2022.
APA Zhao, Xin,Xu, Kaizhe,Ma, Shaodan,Gong, Shiqi,Yang, Guanghua,&Xing, Chengwen.(2022).Joint Transceiver Optimization for IRS-Aided MIMO Communications.IEEE Transactions on Communications.
MLA Zhao, Xin,et al."Joint Transceiver Optimization for IRS-Aided MIMO Communications".IEEE Transactions on Communications (2022).
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