Near-Field LoS/NLoS Channel Estimation for RIS-Aided MU-MIMO Systems: Piece-Wise Low-Rank Approximation Approach

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Hauptverfasser: Lee, Jeongjae, Hong, Songnam
Format: Preprint
Veröffentlicht: 2024
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author Lee, Jeongjae
Hong, Songnam
author_facet Lee, Jeongjae
Hong, Songnam
contents We study the channel estimation problem for a reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) multi-user multiple-input multiple-output (MU-MIMO) system. In particular, it is assumed that the channel between a RIS and a base station (BS) exhibits a near-field line-of-sight (LoS) channel, which is a dominant signal path in mmWave communication systems. Due to the high-rankness and non-sparsity of the RIS-BS channel matrix in our system, the state-of-the-art (SOTA) methods, which are constructed based on far-field or near-field non-LoS (NLoS) channel, cannot provide attractive estimation performances. We for the first time propose an efficient near-field LoS/NLoS channel estimation method for RIS-assisted MU-MIMO systems by means of a piece-wise low-rank approximation. Specifically, an effective channel (to be estimated) is partitioned into piece-wise effective channels containing low-rank structures and then, they are estimated via collaborative low-rank approximation. The proposed method is named PW-CLRA. Via simulations, we verify the effectiveness of the proposed PW-CLRA.
format Preprint
id arxiv_https___arxiv_org_abs_2410_13806
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Near-Field LoS/NLoS Channel Estimation for RIS-Aided MU-MIMO Systems: Piece-Wise Low-Rank Approximation Approach
Lee, Jeongjae
Hong, Songnam
Signal Processing
We study the channel estimation problem for a reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) multi-user multiple-input multiple-output (MU-MIMO) system. In particular, it is assumed that the channel between a RIS and a base station (BS) exhibits a near-field line-of-sight (LoS) channel, which is a dominant signal path in mmWave communication systems. Due to the high-rankness and non-sparsity of the RIS-BS channel matrix in our system, the state-of-the-art (SOTA) methods, which are constructed based on far-field or near-field non-LoS (NLoS) channel, cannot provide attractive estimation performances. We for the first time propose an efficient near-field LoS/NLoS channel estimation method for RIS-assisted MU-MIMO systems by means of a piece-wise low-rank approximation. Specifically, an effective channel (to be estimated) is partitioned into piece-wise effective channels containing low-rank structures and then, they are estimated via collaborative low-rank approximation. The proposed method is named PW-CLRA. Via simulations, we verify the effectiveness of the proposed PW-CLRA.
title Near-Field LoS/NLoS Channel Estimation for RIS-Aided MU-MIMO Systems: Piece-Wise Low-Rank Approximation Approach
topic Signal Processing
url https://arxiv.org/abs/2410.13806