Covariance Difference of Arrival based Fingerprinting Localization

Xinze Li*, Hanan Al-Tous, Salah Eddine Hajri, Olav Tirkkonen

*Corresponding author for this work

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

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Abstract

We define covariance difference of arrival (CDOA) features derived from channel state information that can be used for machine learning based fingerprinting localization in non-line of sight (NLoS) conditions, with minimal communication overhead. Taking advantage of the uniqueness of the multipath channel between the base station (BS) and user equipment (UE) at different locations in the geographical region of interest. UEs compute CDOA features, consisting of pair-wise distances between covariance matrices of received signals from multiple BSs. Measured features are fed back to the network, where fingerprinting localization is performed. We consider both k-nearest neighbour and neural network localization, and investigate the trade-off between localization performance and communication overhead. In simulations of a NLoS 5G NR factory scenario with eight-antenna BSs, CDOA features provide a localization error less than 0.91 m in 80% of the cases, as compared to 0.78 m for a benchmark method where UEs feed back complete measured covariance matrices to the network, and 1.36 m for power difference of arrival features. Comparing to complete covariance feedback, CDOA features reduce communication overhead by 98%.

Original languageEnglish
Title of host publication2023 IEEE 97th Vehicular Technology Conference, VTC 2023-Spring - Proceedings
PublisherIEEE
Number of pages6
ISBN (Electronic)979-8-3503-1114-3
DOIs
Publication statusPublished - 2023
MoE publication typeA4 Conference publication
EventIEEE Vehicular Technology Conference - Florence, Italy, Florence, Italy
Duration: 20 Jun 202323 Jun 2023
Conference number: 97

Publication series

NameIEEE Vehicular Technology Conference
Volume2023-June
ISSN (Print)1550-2252

Conference

ConferenceIEEE Vehicular Technology Conference
Abbreviated titleVTC
Country/TerritoryItaly
CityFlorence
Period20/06/202323/06/2023

Keywords

  • channel state information
  • covariance matrix
  • non-line of sight
  • Wireless localization

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