You, Y., Chen, F., Zhang, L. orcid.org/0000-0002-4535-3200 et al. (2 more authors) (2024) Adaptive Channel Estimation for RIS-Assisted Systems in Time-Varying mmWave Channels. IEEE Transactions on Communications. ISSN 0090-6778
Abstract
To improve channel estimation (CE) for reconfigurable intelligent surface (RIS)-assisted systems in time-varying mmWave channels, this paper proposes a two-stage adaptive CE scheme. This is the first attempt to develop a CE scheme without assumptions on specific timescales for channel variations. In the first stage, the adaptive scheme incorporates the estimation of partial channel state information and a channel status check process. The introduced check process can monitor the changing status of the channels and provide information for the second stage. In the second stage, based on the results from the check process, the adaptive scheme adaptively selects from two proposed candidate CE algorithms: Two-Phase orthogonal matching pursuit (TP-OMP) and Structured-Shift OMP (SS-OMP). Simulation results show that both TP-OMP and SS-OMP can reduce pilot overhead by around 33%, and respectively lower the computational complexity of existing works by about 55% and 65%. Additionally, the check process obtains an accuracy rate of approximately 92% so that the proposed CE scheme can maintain stable CE performance in time-varying channels.
Metadata
Item Type: | Article |
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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. |
Keywords: | Information and Computing Sciences; Communications Engineering; Engineering; Computer Vision and Multimedia Computation |
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: | 28 Aug 2024 12:44 |
Last Modified: | 28 Aug 2024 14:48 |
Published Version: | https://ieeexplore.ieee.org/document/10601593 |
Status: | Published online |
Publisher: | IEEE |
Identification Number: | 10.1109/tcomm.2024.3425592 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:216476 |