ESTIMATION OF CHANNELS IN SYSTEMS WITH INTELLIGENT REFLECTING SURFACES

Michael Joham, Hangze Gao, Wolfgang Utschick

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

We consider channel estimation for systems equipped with an intelligent reflecting surface (IRS). We develop least squares (LS) and minimum mean square error (MMSE) estimation for such systems. The appropriate system models are developed and we also discuss the parameters which can be estimated in such a setup because there exists a difficulty due to the ambiguity for the two channels connecting with the IRS. The MMSE estimator is based on a Kronecker product approximation of the channel covariance matrix. The simulations results illustrate the advantage of the optimized pilots and the optimized phase allocations for the channel estimation.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5368-5372
Number of pages5
ISBN (Electronic)9781665405409
DOIs
StatePublished - 2022
Event47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Virtual, Online, Singapore
Duration: 23 May 202227 May 2022

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2022-May
ISSN (Print)1520-6149

Conference

Conference47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
Country/TerritorySingapore
CityVirtual, Online
Period23/05/2227/05/22

Keywords

  • Intelligent reflecting surfaces
  • channel estimation
  • least squares
  • minimum mean square error
  • pilot optimization

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