An Optimal Channel Estimation Scheme for Intelligent Reflecting Surfaces Based on a Minimum Variance Unbiased Estimator

By Tobias Lindstrøm Jensen, E. de Carvalho. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019

418 citations recorded by the source corpus.

In a wireless system with Intelligent Reflective Surfaces (IRS) containing many passive elements, we consider the problem of channel estimation. All the links from the transmitter to the receiver via each IRS elements (or groups) are estimated. We show that the estimation performance are dependent on the setting of the IRS, and design an optimal channel estimation scheme where the IRS elements follow an optimal series of activation patterns. The optimal design is guided by results for the minimum variance unbiased estimation. The IRS setting during the channel estimation period mimics the discrete Fourier transforms. We show theoretically and with simulations that the estimation variance is one order smaller compared to existing methods with on/off IRS activation patterns as proposed in the literature.

Subfields: Aerospace Engineering, Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/5137587c8288b9bb347f584f712a84aaaa3871f0

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Citations in the corpus

Two-Timescale Channel Estimation for Reconfigurable Intelligent Surface Aided Wireless Communications (2019, methodology): “, dozens to hundreds) of RIS elements and dozens of UEs, while the pilot overhead of typical cascaded channel methods is the product of the number of RIS elements and the number of UEs [4], [5].”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead (2020, positive): “In [88], the authors introduce optimal methods for estimating the cascaded channel from the transmitter to the receiver, i.”
Compressed Channel Estimation for Intelligent Reflecting Surface-Assisted Millimeter Wave Systems (2020, methodology): “For IRSs with all passive elements, least square (LS) estimation methods [8], [9] were proposed to estimate uplink cascade channels.”
Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis (2019, methodology): “On the other hand, [25], [26] proposed a novel discrete Fourier transform (DFT) based channel estimation strategy, in which all the IRS elements are on at each time slot, and their reflection coefficients are determined by the DFT matrix.”
Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey (2019, result): “The authors in [192] propose the optimal activation pattern for the IRS’s channel estimation, which achieves one order lower estimation variance compared to the ON/OFF-based methods.”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead (2020, neutral): “In [88], the authors introduce optimal methods for estimat-”
Intelligent Reflecting Surface-Aided Wireless Communications: A Tutorial (2020, methodology): “To overcome this power loss issue and improve the channel estimation accuracy, the all-ON IRS reflection pattern can be employed with orthogonal reflection coefficients over time, such as those drawn from different columns of an (N + 1)× (N + 1) DFT matrix [61], [90], whereby all the N + 1 channel c”
Intelligent Reflecting Surface-Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design (2020, methodology): “Recently a few papers have proposed LS estimates for the IRS-assisted channels assuming a single-user IRS-assisted MISO system in [23] and [24].”
Reconfigurable Intelligent Surfaces: A signal processing perspective with wireless applications (2021, neutral): “One way to make Ω invertible is to use a scaled DFT matrix [30].”
Channel Estimation for RIS-Empowered Multi-User MISO Wireless Communications (2020, background): “The authors in [27] claimed that they designed an optimal CE scheme, where the RIS unit elements follow an optimal series of activation patterns.”