Joint Precoder, Reflection Coefficients, and Equalizer Design for IRS-Assisted MIMO Systems

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 st...

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Vydané v:	IEEE transactions on communications Ročník 70; číslo 6; s. 4146 - 4161
Hlavní autori:	Zhou, Wen, Xia, Junjuan, Li, Chunguo, Fan, Lisheng, Nallanathan, Arumugam
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.06.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Angle of reflection channel state information (CSI) Data transmission Design optimization Equalizers Error detection Intelligent reflecting surface (IRS) MIMO communication MISO communication multi-input multi-output (MIMO) Optimization Receivers Reflectance Robust design Transceivers Transmission rate (communications) Transmitters Uncertainty Upper bounds Wireless communication systems
ISSN:	0090-6778, 1558-0857
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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.
AbstractList	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.
Author	Li, Chunguo Xia, Junjuan Fan, Lisheng Nallanathan, Arumugam Zhou, Wen
Author_xml	– sequence: 1 givenname: Wen orcidid: 0000-0003-4831-3375 surname: Zhou fullname: Zhou, Wen email: wenzhou@ustc.edu organization: College of Information Science and Technology, Nanjing Forestry University, Nanjing, China – sequence: 2 givenname: Junjuan orcidid: 0000-0003-2787-6582 surname: Xia fullname: Xia, Junjuan email: xiajunjuan@gzhu.edu.cn organization: School of Computer Science, Guangzhou University, Guangzhou, China – sequence: 3 givenname: Chunguo orcidid: 0000-0002-4689-7226 surname: Li fullname: Li, Chunguo email: chunguoli@seu.edu.cn organization: School of Information Science and Engineering, Southeast University, Nanjing, China – sequence: 4 givenname: Lisheng orcidid: 0000-0002-9783-1366 surname: Fan fullname: Fan, Lisheng email: lsfan@gzhu.edu.cn organization: School of Computer Science, Guangzhou University, Guangzhou, China – sequence: 5 givenname: Arumugam orcidid: 0000-0001-8337-5884 surname: Nallanathan fullname: Nallanathan, Arumugam email: a.nallanathan@qmul.ac.uk organization: School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K
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SubjectTerms	Angle of reflection channel state information (CSI) Data transmission Design optimization Equalizers Error detection Intelligent reflecting surface (IRS) MIMO communication MISO communication multi-input multi-output (MIMO) Optimization Receivers Reflectance Robust design Transceivers Transmission rate (communications) Transmitters Uncertainty Upper bounds Wireless communication systems
Title	Joint Precoder, Reflection Coefficients, and Equalizer Design for IRS-Assisted MIMO Systems
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