Matrix-Calibration-Based Cascaded Channel Estimation for Reconfigurable Intelligent Surface Assisted Multiuser MIMO

By Hang Liu, Xiaojun Yuan, Ying-Jun Angela Zhang. IEEE Journal on Selected Areas in Communications, 2019

318 citations recorded by the source corpus.

Reconfigurable intelligent surface (RIS) is envisioned to be an essential component of the paradigm for beyond 5G networks as it can potentially provide similar or higher array gains with much lower hardware cost and energy consumption compared with the massive multiple-input multiple-output (MIMO) technology. In this paper, we focus on one of the fundamental challenges, namely the channel acquisition, in a RIS-assisted multiuser MIMO system. The state-of-the-art channel acquisition approach in such a system with fully passive RIS elements estimates the cascaded transmitter-to-RIS and RIS-to-receiver channels by adopting excessively long training sequences. To estimate the cascaded channels with an affordable training overhead, we formulate the channel estimation problem in the RIS-assisted multiuser MIMO system as a matrix-calibration based matrix factorization task. By exploiting the information on the slow-varying channel components and the hidden channel sparsity, we propose a novel message-passing based algorithm to factorize the cascaded channels. Furthermore, we present an analytical framework to characterize the theoretical performance bound of the proposed estimator in the large-system limit. Finally, we conduct simulations to verify the high accuracy and efficiency of the proposed algorithm.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/2bfff884ada44ef38be035b1d1b0df5c25a16952

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In Electrical and Electronic Engineering

Citations in the corpus

Intelligent Reflecting Surface-Aided Wireless Communications: A Tutorial (2020, methodology): “Cascaded channel decomposition/factorization for the IRS-aided MIMO/MISO system [97], [98]”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead (2020, methodology): “In [96], the authors formulate the channel estimation problem of an RIS-assisted multiuser MIMO system as a matrix-calibration based matrix factorization task.”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead (2020, methodology): “In [96], the authors formulate the channel estimation problem of an RIS-assisted multiuser MIMO system as a matrixcalibration based matrix factorization task.”
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications (2021, background): “To address this unique challenge, the common reflective channels among all edge devices [281], quasi-static property between RIS and edge server channel links [282], [283], spatial features of”
RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trials (2021, methodology): “The RIS beamforming conﬁguration problem has been analyzed mathematically in a series of previous works [29], [30]; we refer to [9] for a recent survey.”