Zhao, W., Dai, Y., You, Y. et al. (3 more authors) (2024) Efficient Data Transmission With Compressed Channel Estimation in RIS-Assisted mmWave MIMO Systems. IEEE Wireless Communications Letters. ISSN 2162-2337
Abstract
To improve wireless connectivity, reconfigurable intelligent surface (RIS) offers an energy-efficient solution in millimeter wave (mmWave) multi-input multi-output (MIMO) systems. However, the achievable spectrum efficiency (SE) has been limited by challenges associated with channel estimation (CE) and hybrid beamforming design. To address these issues, we propose an efficient data transmission (DT) scheme with two-stage compressed sensing (CS)-based CE by exploiting the sparse angular domain channel structure and pruning insignificant components. Simulation results demonstrate that the proposed method achieves reduction in pilot overhead and complexity of CE, and higher SE of DT via iterative optimization.
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: | Theory Of Computation; Engineering; Information and Computing Sciences; Communications Engineering; Computer Vision and Multimedia Computation; Data Management and Data Science; Affordable and Clean Energy |
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: | 30 Aug 2024 10:50 |
Last Modified: | 30 Aug 2024 10:50 |
Published Version: | https://ieeexplore.ieee.org/document/10589430 |
Status: | Published online |
Publisher: | IEEE |
Identification Number: | 10.1109/lwc.2024.3425150 |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:216566 |