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

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10 Citations (Scopus)

Abstract

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.
Original languageEnglish
Title of host publicationICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Number of pages5
PublisherIEEE
Publication date9 Apr 2020
Pages5000-5004
Article number9053695
ISBN (Print)978-1-5090-6632-2
ISBN (Electronic)978-1-5090-6631-5
DOIs
Publication statusPublished - 9 Apr 2020
EventICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Barcelona, Spain
Duration: 4 May 20208 May 2020

Conference

ConferenceICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
CountrySpain
CityBarcelona
Period04/05/202008/05/2020
SeriesICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN1520-6149

Keywords

  • Channel Estimation
  • Intelligent Reflecting Surfaces
  • Least Squares
  • Minimum Variance Unbiased Estimator

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