Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications

Zhaorui Wang, Liang Liu, Shuguang Cui

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

56 Citations (Scopus)


In the intelligent reflecting surface (IRS) assisted communication systems, the acquisition of channel state information (CSI) is a crucial impediment for achieving the passive beamforming gain of IRS because of the considerable overhead required for channel estimation. Specifically, under the current beamforming design for IRS-assisted communications, {KMN} + KM channel coefficients should be estimated if the passive IRS cannot estimate its channels with the base station (BS) and users due to its lack of radio frequency (RF) chains, where K, N and M denote the numbers of users, reflecting elements of the IRS, and antennas at the BS, respectively. These numbers can be extremely large in practice considering the current trend of massive MIMO (multiple-input multiple-output), i.e., a large M, and massive connectivity, i.e., a large K. To accurately estimate such a large number of channel coefficients within a short time interval, we devote our endeavour in this paper to investigating the efficient pilot-based channel estimation method in IRS-assisted uplink communications. Building upon the observation that each IRS element reflects the signals from all the users to the BS via the same channel, we analytically verify that a time duration consisting of K+N+\max \left(K-1,\left\lceil\frac{(K-1) N}{M}\right\rceil\right) pilot symbols is sufficient for the BS to perfectly recover all the KMN+KM channel coefficients for the case without receiver noise. In contrast to the conventional uplink communications without IRS in which the minimum pilot sequence length is independent with the number of receive antennas, our study reveals the significant role of massive MIMO in reducing the channel training time for IRS-assisted communications.

Original languageEnglish
Title of host publication2020 IEEE Wireless Communications and Networking Conference, WCNC 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728131061
Publication statusPublished - May 2020
Event2020 IEEE Wireless Communications and Networking Conference, WCNC 2020 - Seoul, Korea, Republic of
Duration: 25 May 202028 May 2020

Publication series

NameIEEE Wireless Communications and Networking Conference, WCNC
ISSN (Print)1525-3511


Conference2020 IEEE Wireless Communications and Networking Conference, WCNC 2020
Country/TerritoryKorea, Republic of

ASJC Scopus subject areas

  • Engineering(all)


Dive into the research topics of 'Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications'. Together they form a unique fingerprint.

Cite this