HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Journal articles

Channel Estimation for Intelligent Reflecting Surface Assisted MIMO Systems: A Tensor Modeling Approach

Abstract : Intelligent reflecting surface (IRS) is an emerging technology for future wireless communications including 5G and especially 6G. It consists of a large 2D array of (semi-)passive scattering elements that control the electromagnetic properties of radio-frequency waves so that the reflected signals add coherently at the intended receiver or destructively to reduce co-channel interference. The promised gains of IRS-assisted communications depend on the accuracy of the channel state information. In this paper, we address the receiver design for an IRS-assisted multiple-input multiple-output (MIMO) communication system via a tensor modeling approach aiming at the channel estimation problem using supervised (pilot-assisted) methods. Considering a structured time-domain pattern of pilots and IRS phase shifts, we present two channel estimation methods that rely on a parallel factor (PARAFAC) tensor modeling of the received signals. The first one has a closed-form solution based on a Khatri-Rao factorization of the cascaded MIMO channel, by solving rank-1 matrix approximation problems, while the second on is an iterative alternating estimation scheme. The common feature of both methods is the decoupling of the estimates of the involved MIMO channel matrices (base station-IRS and IRS-user terminal), which provides performance enhancements in comparison to competing methods that are based on unstructured LS estimates of the cascaded channel. Design recommendations for both methods that guide the choice of the system parameters are discussed. Numerical results show the effectiveness of the proposed receivers, highlight the involved trade-offs, and corroborate their superior performance compared to competing LS-based solutions.
Document type :
Journal articles
Complete list of metadata

https://hal.univ-lille.fr/hal-03146480
Contributor : Remy Boyer Connect in order to contact the contributor
Submitted on : Friday, February 19, 2021 - 10:12:27 AM
Last modification on : Friday, April 1, 2022 - 3:48:48 AM
Long-term archiving on: : Thursday, May 20, 2021 - 6:23:26 PM

File

final_manuscript.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-03146480, version 1

Collections

Citation

Gilderlan de Araújo, André de Almeida, Remy Boyer. Channel Estimation for Intelligent Reflecting Surface Assisted MIMO Systems: A Tensor Modeling Approach. IEEE Journal of Selected Topics in Signal Processing, IEEE, 2021, 15 (3), pp.789-802. ⟨hal-03146480⟩

Share

Metrics

Record views

70

Files downloads

146