You, Y and Zhang, L orcid.org/0000-0002-4535-3200 (2022) Off-grid Compressive Sensing Based Channel Estimation with Non-uniform Grid in Millimeter Wave MIMO System. In: 2022 16th European Conference on Antennas and Propagation (EuCAP). EuCAP 2022, 27 Mar - 01 Apr 2022, Madrid, Spain. IEEE ISBN 978-1-6654-1604-7
Abstract
Channel estimation is challenging for millimeter-wave (mmWave) communications because of the use of hybrid architecture and massive multiple-input multiple-output (MIMO) technology. By utilizing the sparsity in the angular domain, conventional on-grid compressive sensing methods can efficiently recover the channel state information (CSI). However, the channel estimation accuracy is severely affected by the off-grid errors and the selection of grid angles. The off-grid compressive sensing methods and the non-uniform grid angles can improve the channel estimation accuracy. In this paper, we investigate the impact of the non-uniform grid angles for the off-grid compressive sensing methods and the on-grid compressive sensing methods. We propose to employ the orthogonal matching pursuit (OMP) algorithm with interior point (IP) method based off-grid error mitigation to implement the channel estimation using the selected angle design. The simulation results demonstrate the advantages of the proposed off-grid compressive sensing method and show the impact of the non-uniform grid angles.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022, 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: | channel estimation , compressive sensing , optimization methods , off-grid errors |
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: | 07 Jan 2022 13:14 |
Last Modified: | 27 May 2022 15:09 |
Published Version: | https://ieeexplore.ieee.org/document/9769416 |
Status: | Published |
Publisher: | IEEE |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:182181 |