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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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 |
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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 |
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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. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Zhang, Wei Tay, Wee Peng |
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Article |
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Zhang, Wei Tay, Wee Peng |
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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 |
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Cost-efficient RIS-aided channel estimation via rank-one matrix factorization |
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Cost-efficient RIS-aided channel estimation via rank-one matrix factorization |
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cost-efficient ris-aided channel estimation via rank-one matrix factorization |
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2021 |
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https://hdl.handle.net/10356/152711 |
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