Capacity Characterization for Intelligent Reflecting Surface Aided MIMO Communication
Intelligent reflecting surface (IRS) is a promising solution to enhance the wireless communication capacity both cost-effectively and energy-efficiently, by properly altering the signal propagation via tuning a large number of passive reflecting units. In this paper, we aim to characterize the funda...
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| Published in | IEEE journal on selected areas in communications Vol. 38; no. 8; pp. 1823 - 1838 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.08.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Intelligent reflecting surface (IRS) is a promising solution to enhance the wireless communication capacity both cost-effectively and energy-efficiently, by properly altering the signal propagation via tuning a large number of passive reflecting units. In this paper, we aim to characterize the fundamental capacity limit of IRS-aided point-to-point multiple-input multiple-output (MIMO) communication systems with multi-antenna transmitter and receiver in general, by jointly optimizing the IRS reflection coefficients and the MIMO transmit covariance matrix. First, we consider narrowband transmission under frequency-flat fading channels, and develop an efficient alternating optimization algorithm to find a locally optimal solution by iteratively optimizing the transmit covariance matrix or one of the reflection coefficients with the others being fixed. Next, we consider capacity maximization for broadband transmission in a general MIMO orthogonal frequency division multiplexing (OFDM) system under frequency-selective fading channels, where transmit covariance matrices are optimized for different subcarriers while only one common set of IRS reflection coefficients is designed to cater to all the subcarriers. To tackle this more challenging problem, we propose a new alternating optimization algorithm based on convex relaxation to find a high-quality suboptimal solution. Numerical results show that our proposed algorithms achieve substantially increased capacity compared to traditional MIMO channels without the IRS, and also outperform various benchmark schemes. In particular, it is shown that with the proposed algorithms, various key parameters of the IRS-aided MIMO channel such as channel total power, rank, and condition number can be significantly improved for capacity enhancement. |
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| AbstractList | Intelligent reflecting surface (IRS) is a promising solution to enhance the wireless communication capacity both cost-effectively and energy-efficiently, by properly altering the signal propagation via tuning a large number of passive reflecting units. In this paper, we aim to characterize the fundamental capacity limit of IRS-aided point-to-point multiple-input multiple-output (MIMO) communication systems with multi-antenna transmitter and receiver in general, by jointly optimizing the IRS reflection coefficients and the MIMO transmit covariance matrix. First, we consider narrowband transmission under frequency-flat fading channels, and develop an efficient alternating optimization algorithm to find a locally optimal solution by iteratively optimizing the transmit covariance matrix or one of the reflection coefficients with the others being fixed. Next, we consider capacity maximization for broadband transmission in a general MIMO orthogonal frequency division multiplexing (OFDM) system under frequency-selective fading channels, where transmit covariance matrices are optimized for different subcarriers while only one common set of IRS reflection coefficients is designed to cater to all the subcarriers. To tackle this more challenging problem, we propose a new alternating optimization algorithm based on convex relaxation to find a high-quality suboptimal solution. Numerical results show that our proposed algorithms achieve substantially increased capacity compared to traditional MIMO channels without the IRS, and also outperform various benchmark schemes. In particular, it is shown that with the proposed algorithms, various key parameters of the IRS-aided MIMO channel such as channel total power, rank, and condition number can be significantly improved for capacity enhancement. |
| Author | Zhang, Shuowen Zhang, Rui |
| Author_xml | – sequence: 1 givenname: Shuowen orcidid: 0000-0002-4511-4154 surname: Zhang fullname: Zhang, Shuowen email: elezhsh@nus.edu.sg organization: Department of Electrical and Computer Engineering, National University of Singapore, Singapore – sequence: 2 givenname: Rui orcidid: 0000-0002-8729-8393 surname: Zhang fullname: Zhang, Rui email: elezhang@nus.edu.sg organization: Department of Electrical and Computer Engineering, National University of Singapore, Singapore |
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| CODEN | ISACEM |
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| SubjectTerms | Algorithms alternating optimization Broadband capacity Channels Coefficients Communication Communications systems Covariance matrices Covariance matrix Intelligent reflecting surface (IRS) MIMO communication multiple-input multiple-output (MIMO) Narrowband OFDM Optimization Optimization algorithms Orthogonal Frequency Division Multiplexing passive reflection Receivers Reconfigurable intelligent surfaces Reflection Selective fading Subcarriers Transmitters Wireless communications |
| Title | Capacity Characterization for Intelligent Reflecting Surface Aided MIMO Communication |
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