How Should IRSs Scale to Harden Multi-Antenna Channels?

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

  • Ali Bereyhi - , Friedrich-Alexander University Erlangen-Nürnberg (Author)
  • Saba Asaad - , Friedrich-Alexander University Erlangen-Nürnberg (Author)
  • Chongjun Ouyang - , Beijing University of Posts and Telecommunications (Author)
  • Ralf R. Muller - , Friedrich-Alexander University Erlangen-Nürnberg (Author)
  • Rafael F. Schaefer - , University of Siegen (Author)
  • H. Vincent Poor - , Princeton University (Author)

Abstract

This work extends the concept of channel hardening to multi-antenna systems that are aided by intelligent reflecting surfaces (IRSs). For fading links between a multi-antenna transmitter and a single-antenna receiver, we derive an accurate approximation for the distribution of the input-output mutual information when the number of reflecting elements grows large. The asymptotic results demonstrate that by increasing the number of elements on the IRS, the end-to-end channel hardens as long as the physical dimensions of the IRS grow as well. The growth rate however need not to be of a specific order and can be significantly sub-linear. The validity of the analytical result is confirmed by numerical experiments.

Details

Original languageEnglish
Title of host publication2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop, SAM 2022
PublisherIEEE Computer Society
Pages276-280
Number of pages5
ISBN (electronic)978-1-6654-0633-8
Publication statusPublished - 2022
Peer-reviewedYes
Externally publishedYes

Publication series

SeriesSensor Array and Multichannel Signal Processing Workshop
Volume2022-June

Conference

Title12th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2022
Duration20 - 23 June 2022
CityTrondheim
CountryNorway

External IDs

ORCID /0000-0002-1702-9075/work/165878345

Keywords

Keywords

  • channel hardening, Intelligent reflecting surfaces, large-system analysis