Cost-efficient RIS-aided channel estimation via rank-one matrix factorization

A reconfigurable intelligent surface (RIS) consists of massive meta elements, which can improve the performance of future wireless communication systems. Existing RIS-aided channel estimation methods try to estimate the cascaded channel directly, incurring high computational and training overhead es...

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Main Authors: Zhang, Wei, Tay, Wee Peng
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/152711
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1527112021-12-08T11:27:43Z Cost-efficient RIS-aided channel estimation via rank-one matrix factorization Zhang, Wei Tay, Wee Peng School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering::Wireless communication systems Channel Estimation Matrix Factorization A reconfigurable intelligent surface (RIS) consists of massive meta elements, which can improve the performance of future wireless communication systems. Existing RIS-aided channel estimation methods try to estimate the cascaded channel directly, incurring high computational and training overhead especially when the number of elements of RIS is extremely large. In this paper, we propose a cost-efficient channel estimation method via rank-one matrix factorization (MF). Specifically, if the RIS is employed near base station (BS), it is found that the RIS-aided channel can be factorized into a product of low-dimensional matrices. To estimate these factorized matrices, we propose alternating minimization and gradient descent approaches to obtain the near optimal solutions. Compared to directly estimating the cascaded channel, the proposed MF method reduces training overhead substantially. Finally, the numerical simulations show the effectiveness of the proposed MF method. Agency for Science, Technology and Research (A*STAR) Accepted version This research is supported by A*STAR under its RIE2020 Advanced Manufacturing and Engineering (AME) Industry Alignment Fund Pre Positioning (IAF-PP) (Grant No. A19D6a0053). 2021-12-08T11:27:42Z 2021-12-08T11:27:42Z 2021 Journal Article Zhang, W. & Tay, W. P. (2021). Cost-efficient RIS-aided channel estimation via rank-one matrix factorization. IEEE Wireless Communications Letters, 10(11), 2562-2566. https://dx.doi.org/10.1109/LWC.2021.3107547 2162-2337 https://hdl.handle.net/10356/152711 10.1109/LWC.2021.3107547 2-s2.0-85114621638 11 10 2562 2566 en A19D6a0053 IEEE Wireless Communications Letters © 2021 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. The published version is available at: https://doi.org/10.1109/LWC.2021.3107547. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering::Wireless communication systems
Channel Estimation
Matrix Factorization
spellingShingle Engineering::Electrical and electronic engineering::Wireless communication systems
Channel Estimation
Matrix Factorization
Zhang, Wei
Tay, Wee Peng
Cost-efficient RIS-aided channel estimation via rank-one matrix factorization
description A reconfigurable intelligent surface (RIS) consists of massive meta elements, which can improve the performance of future wireless communication systems. Existing RIS-aided channel estimation methods try to estimate the cascaded channel directly, incurring high computational and training overhead especially when the number of elements of RIS is extremely large. In this paper, we propose a cost-efficient channel estimation method via rank-one matrix factorization (MF). Specifically, if the RIS is employed near base station (BS), it is found that the RIS-aided channel can be factorized into a product of low-dimensional matrices. To estimate these factorized matrices, we propose alternating minimization and gradient descent approaches to obtain the near optimal solutions. Compared to directly estimating the cascaded channel, the proposed MF method reduces training overhead substantially. Finally, the numerical simulations show the effectiveness of the proposed MF method.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Zhang, Wei
Tay, Wee Peng
format Article
author Zhang, Wei
Tay, Wee Peng
author_sort Zhang, Wei
title Cost-efficient RIS-aided channel estimation via rank-one matrix factorization
title_short Cost-efficient RIS-aided channel estimation via rank-one matrix factorization
title_full Cost-efficient RIS-aided channel estimation via rank-one matrix factorization
title_fullStr Cost-efficient RIS-aided channel estimation via rank-one matrix factorization
title_full_unstemmed Cost-efficient RIS-aided channel estimation via rank-one matrix factorization
title_sort cost-efficient ris-aided channel estimation via rank-one matrix factorization
publishDate 2021
url https://hdl.handle.net/10356/152711
_version_ 1718928702535892992