Double intelligent reflecting surface-assisted multi-user MIMO mmWave systems with hybrid precoding
Article
Niu, H., Chu, Z., Zhou, F., Pan, C., Ng, D. and Nguyen, H. 2022. Double intelligent reflecting surface-assisted multi-user MIMO mmWave systems with hybrid precoding. IEEE Transactions on Vehicular Technology. 71 (2), pp. 1575-1587. https://doi.org/10.1109/TVT.2021.3131514
Type | Article |
---|---|
Title | Double intelligent reflecting surface-assisted multi-user MIMO mmWave systems with hybrid precoding |
Authors | Niu, H., Chu, Z., Zhou, F., Pan, C., Ng, D. and Nguyen, H. |
Abstract | This work investigates the effect of double intelligent reflecting surface (IRS) in improving the spectrum efficient of multi-user multiple-input multiple-output (MIMO) network operating in the millimeter wave (mmWave) band. Specifically, we aim to solve a weighted sum rate maximization problem by jointly optimizing the digital precoding at the transmitter and the analog phase shifters at the IRS, subject to the minimum achievable rate constraint. To facilitate the design of an efficient solution, we first reformulate the original problem into a tractable one by exploiting the majorization-minimization (MM) method. Then, a block coordinate descent (BCD) method is proposed to obtain a suboptimal solution, where the precoding matrices and the phase shifters are alternately optimized. Specifically, the digital precoding matrix design problem is solved by the quadratically constrained quadratic programming (QCQP), while the analog phase shift optimization is solved by the Riemannian manifold optimization (RMO). The convergence and computational complexity are analyzed. Finally, simulation results are provided to verify the performance of the proposed design, as well as the effectiveness of double-IRS in improving the spectral efficiency. |
Keywords | Precoding; MIMO communication; Optimization; MISO communication; Quality of service; Phase shifters; Simulation; Intelligent reflecting surface; mmWave communications; hybrid precoding; majorization-minimization; Riemannian manifold optimization |
Publisher | IEEE |
Journal | IEEE Transactions on Vehicular Technology |
ISSN | 0018-9545 |
Electronic | 1939-9359 |
Publication dates | |
Online | 30 Nov 2021 |
14 Feb 2022 | |
Publication process dates | |
Deposited | 15 Dec 2021 |
Accepted | 25 Nov 2021 |
Submitted | 29 Jun 2021 |
Output status | Published |
Accepted author manuscript | File Access Level Open |
Copyright Statement | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TVT.2021.3131514 |
Web of Science identifier | WOS:000756861400039 |
Language | English |
https://repository.mdx.ac.uk/item/89982
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