Fast Ambiguity-Free Subspace-Based Multiple AoA Estimation for Hybrid Linear Arrays

Wei Cheng Kao*, Jwo Yuh Wu, Shang Ho Tsai, Tsang Yi Wang

*Corresponding author for this work

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

Abstract

Angle-of-arrival (AoA) estimation via hybrid uniform linear arrays is subject to inherent ambiguity incurred by mixing many subarray measurements into just few RF chains. With the aid of non-uniform subarray placement, this paper proposes a low-complexity beam-space MUSIC algorithm capable of achieving ambiguity-free multiple AoA estimation. An ambiguity-free condition, specified by inter-subarray spacings, is derived, leading to various array configurations guaranteeing unique AoA recovery. Simulation results show that our proposed approach compares favorably with an existing temporal-domain based MUSIC method at reduced computational complexity.

Original languageEnglish
Title of host publication2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications
Subtitle of host publication6G The Next Horizon - From Connected People and Things to Connected Intelligence, PIMRC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665464833
DOIs
StatePublished - 2023
Event34th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2023 - Toronto, Canada
Duration: 5 Sep 20238 Sep 2023

Publication series

NameIEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC

Conference

Conference34th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2023
Country/TerritoryCanada
CityToronto
Period5/09/238/09/23

Keywords

  • AoA estimation
  • hybrid array
  • MUSIC

Fingerprint

Dive into the research topics of 'Fast Ambiguity-Free Subspace-Based Multiple AoA Estimation for Hybrid Linear Arrays'. Together they form a unique fingerprint.

Cite this