You, Y., Zhao, W., Zhang, L. orcid.org/0000-0002-4535-3200 et al. (2 more authors) (2024) Beam Pattern and Reflection Pattern Design for Channel Estimation in RIS-assisted mmWave MIMO Systems. IEEE Transactions on Vehicular Technology, 73 (4). pp. 5915-5919. ISSN 0018-9545
Abstract
Reconfigurable intelligent surface (RIS) is a revolutionary technology that can be applied in millimeter wave (mmWave) communications to reduce the high power consumption and propagation loss. However, channel estimation (CE) is challenging due to the large number of passive RIS elements without signal processing abilities. In this paper, the uplink CE for RIS-assisted mmWave multi-input multi-output (MIMO) systems is formulated as a sparse signal recovery problem in a novel way. Then, the beam pattern and reflection pattern design based on the compressed sensing (CS) theory are proposed to guarantee the efficient CE. Simulation results demonstrate that, for various CS-based CE algorithms, the proposed patterns can reduce more than 50% pilot overhead at 0 dB signal-to-noise ratio (SNR) while maintaining the same accuracy of CE compared with the existing patterns.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 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. |
Keywords: | Reconfigurable intelligent surface (RIS), channel estimation (CE), pilot beam pattern design, reflection design |
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: | 22 Jan 2024 14:55 |
Last Modified: | 23 May 2024 14:20 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/tvt.2023.3309950 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:208073 |