You, Y, Xue, Y, Zhang, L orcid.org/0000-0002-4535-3200 et al. (3 more authors) (2023) Channel Estimation for RIS Assisted Millimeter Wave Systems via OMP with Optimization. IEEE Transactions on Vehicular Technology, 72 (12). pp. 16783-16787. ISSN 0018-9545
Abstract
Reconfigurable intelligence surface (RIS) can be deployed to assist the communications in millimeter wave (mmWave) systems. Employing the sparsity of the mmWave channel, the compressive sensing (CS) techniques can be leveraged to reduce the pilot overhead of the channel estimation (CE). However, conventional CS-based algorithms are based on the discrete grids and the difference between the real continuous angle and its nearest grid point is called off-grid error. Off-grid errors seriously deteriorate the CE performance. In this paper, we propose the orthogonal matching pursuit with discrete-continuous optimization (DC-OMP) method for RIS assisted mmWave systems to mitigate the impact of the off-grid errors. Simulation results show that compared with existing works, the proposed DC-OMP can efficiently mitigate the impact of the off-grid errors without adding much complexity.
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 intelligence surface (RIS), channel estimation (CE), compressive sensing (CS), orthogonal matching pursuit (OMP), optimization |
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: | 16 Mar 2023 15:14 |
Last Modified: | 23 May 2024 14:17 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/TVT.2023.3290398 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:197339 |