Chen, X., Gautam, P. and Zhang, L. orcid.org/0000-0002-4535-3200 (2024) Low-complexity Phase Shifter Design for Reconfigurable Intelligent Surface Aided mmWave Massive MIMO Systems. In: Proceedings of IEEE Wireless Communications and Networking Conference. 2024 IEEE Wireless Communications and Networking Conference (WCNC), 21-24 Apr 2024, Dubai, UAE. IEEE ISBN 979-8-3503-0359-9
Abstract
Lately, Reconfigurable Intelligent Surface (RIS) is becoming an emerging technique that supports wireless communications with higher transmission quality via adjustable propagation environment. To fully actualize its functionality, the design of its phase shifter (PS) is critical. However, most existing RIS PS design methods and algorithms are very complex and consume considerable processing time, which is unfavorable for the efficient real-time communication systems. In this paper, we aim to realize low-complexity joint optimization for precoder, combiner and RIS PS. We consider a RIS-aided point-to-point (P2P) millimeter-wave (mmWave) fully digital massive Multiple-Input-Multiple-Output (MIMO) downlink system. When designing the RIS PS, we employ the method of minimizing mean square error (MMSE) between the transmitted and received signals. To reduce computational complexity, the non-convex MMSE problem is converted to a convex trace maximization problem under the application of MMSE combiner and SVD precoder. The closed-form solution for RIS subproblem is derived, and a low-complexity alternative joint optimization algorithm is proposed. The simulation results show that the proposed algorithm can achieve high spectrum efficiency in comparison with the state-of-the-art methods, requiring much less computational complexity, as demonstrated by complexity analysis and runtime comparison.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 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. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Jan 2024 10:34 |
Last Modified: | 31 Jul 2024 13:20 |
Published Version: | https://ieeexplore.ieee.org/document/10570534 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/WCNC57260.2024.10570534 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:207948 |