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dc.contributor.authorZhang, Weien_US
dc.contributor.authorTay, Wee Pengen_US
dc.identifier.citationZhang, W. & Tay, W. P. (2021). Cost-efficient RIS-aided channel estimation via rank-one matrix factorization. IEEE Wireless Communications Letters, 10(11), 2562-2566.
dc.description.abstractA 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.en_US
dc.description.sponsorshipAgency for Science, Technology and Research (A*STAR)en_US
dc.relation.ispartofIEEE Wireless Communications Lettersen_US
dc.rights© 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:
dc.subjectEngineering::Electrical and electronic engineering::Wireless communication systemsen_US
dc.titleCost-efficient RIS-aided channel estimation via rank-one matrix factorizationen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.versionAccepted versionen_US
dc.subject.keywordsChannel Estimationen_US
dc.subject.keywordsMatrix Factorizationen_US
dc.description.acknowledgementThis research is supported by A*STAR under its RIE2020 Advanced Manufacturing and Engineering (AME) Industry Alignment Fund Pre Positioning (IAF-PP) (Grant No. A19D6a0053).en_US
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