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Cited by 914

The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.

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

Open access
Wang, Zhaorui, Liu, Liang, Cui, Shuguang·2020·IEEE Transactions on Wireless Communications
DOI 10.1109/twc.2020.3004330
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Abstract

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 KMN+KM channel coefficients should be estimated, where K, N and M 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 userBS 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 K + N + max(K - 1, [(K - 1)N/M]) pilot symbols is sufficient for perfectly recovering all the KMN + KM 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.

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Research works printed but not linked: 2

  1. Larsson, 2020, Intelligent Reflecting Surfaces: On Use Cases and Path Loss Model
  2. 10.1109/4234.951380 · doi:10.1109/4234.951380

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Metadata

Authors
Wang, Z., Liu, L., & Cui, S.
Venue
IEEE Transactions on Wireless Communications
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2020-10
Volume
19
Issue
10
Pages
6607-6620
ISSN
  • 1536-1276 (ISSN-L)
  • 1558-2248
DOI
10.1109/twc.2020.3004330
OpenAlex
W3039402952
Cited by
914
References
30
FWCI
47.68
Type
journal article
Language
en
Open access
green
Licence
Funders
  • The Hong Kong Polytechnic University (P0030001)
  • Key Area Research and Development Program of Guangdong Province (2018B030338001)
  • National Key Research and Development Program of China (2018YFB1800800)
  • Natural Science Foundation of China (NSFC-61629101)
  • Guangdong Zhujiang Project (2017ZT07X152)

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CoChat. (2026). Citation check: Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis. https://app.cochat.ai/papers/10.1109/twc.2020.3004330
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Wang, Z., Liu, L., & Cui, S. (2020). Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis. IEEE Transactions on Wireless Communications. https://doi.org/10.1109/twc.2020.3004330

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