Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis

By Zhaorui Wang, Liang Liu, Shuguang Cui. IEEE Transactions on Wireless Communications, 2019

851 citations recorded by the source corpus.

In intelligent reflecting surface (IRS) assisted communication systems, the acquisition of channel state information is a crucial impediment for achieving the beamforming gain of IRS because of the considerable overhead required for channel estimation. Specifically, under the current beamforming design for IRS-assisted communications, in total <inline-formula> <tex-math notation="LaTeX">$KMN+KM$ </tex-math></inline-formula> channel coefficients should be estimated, where <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> denote the numbers of users, IRS reflecting elements, and antennas at the base station (BS), respectively. For the first time in the literature, this paper points out that despite the vast number of channel coefficients that should be estimated, significant redundancy exists in the user-IRS-BS reflected channels of different users arising from the fact that each IRS element reflects the signals from all the users to the BS via the same channel. To utilize this redundancy for reducing the channel estimation time, we propose a novel three-phase pilot-based channel estimation framework for IRS-assisted uplink multiuser communications, in which the user-BS direct channels and the user-IRS-BS reflected channels of a typical user are estimated in Phase I and Phase II, respectively, while the user-IRS-BS reflected channels of the other users are estimated with low overhead in Phase III via leveraging their strong correlation with those of the typical user. Under this framework, we analytically prove that a time duration consisting of <inline-formula> <tex-math notation="LaTeX">$K+N+\max (K-1,\lceil (K-1)N/M \rceil)$ </tex-math></inline-formula> pilot symbols is sufficient for perfectly recovering all the <inline-formula> <tex-math notation="LaTeX">$KMN+KM$ </tex-math></inline-formula> channel coefficients under the case without receiver noise at the BS. Further, under the case with receiver noise, the user pilot sequences, IRS reflecting coefficients, and BS linear minimum mean-squared error channel estimators are characterized in closed-form.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4d56a8eafc6b97579c0bcf7d6fd4ab211e26cee3

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Citations in the corpus

RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trials (2021, neutral): “In previous literature, the RIS configuration is generally divided into two disjoint subproblems: 1) selecting an SNRmaximizing configuration when having full Channel State Information (CSI) [10], [11]; 2) Acquiring CSI from explicit pilot signals [29]–[31].”
Robust and Secure Wireless Communications via Intelligent Reflecting Surfaces (2019, background): “, quantization errors of the phase shifts at the IRSs [35], noisy estimation [36], and outdated feedback.”
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”
Intelligent Reflecting Surface-Aided Wireless Communications: A Tutorial (2020, methodology): “Note that different from [106] that exploits the redundancy of receive antennas at the BS for training overhead reduction, [83] exploits the redundancy of OFDM sub-carriers to support more users for concurrent channel estimation and thus improve the training efficiency, which is applicable to all th”
Two-Timescale Channel Estimation for Reconfigurable Intelligent Surface Aided Wireless Communications (2019, methodology): “In [14], the authors propose an ingenious method to reduce the pilot overhead.”
An Overview of Signal Processing Techniques for RIS/IRS-Aided Wireless Systems (2021, positive): “In [52], the authors exploited the common RIS-BS channel and proposed a novel three-stage channel estimation algorithm.”
Prospective Multiple Antenna Technologies for Beyond 5G (2019, methodology): “In [173], a tailor-made three-phase pilot-based channel estimation framework was designed to estimate the overall uplink channels in an IRS system.”
Reconfigurable Intelligent Surfaces: Three Myths and Two Critical Questions (2020, methodology): “An estimation algorithm exploiting this correlation is proposed in [14].”
Joint Transmit Waveform and Passive Beamforming Design for RIS-Aided DFRC Systems (2021, methodology): “In addition, channel state information (CSI) acquisition, which is a crucial and challenging task in RIS-aided wireless systems, has been intensively investigated and comprehensively reviewed in [25]-[27].”