User-Side Indoor Localization Using CSI Fingerprinting

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

1 Sitaatiot (Scopus)
78 Lataukset (Pure)

Abstrakti

We consider a scalable User Equipment (UE)-side indoor localization framework that processes Channel State Information (CSI) from multiple Access Points (APs). We use CSI features that are resilient to synchronization errors and other hardware impairments. As a consequence our method does not require accurate network synchronization among APs. Increasing the number of APs considered by a UE profoundly improves fingerprint positioning, with the cost of increasing complexity and channel estimation time. In order to improve scalability of the framework to large networks consisting of multiple APs in many rooms, we train a multi-layer neural network that combines CSI features and unique AP identifiers of a subset of APs in range of a UE. We simulate UE-side localization using CSI obtained from a commercial raytracer. The considered method processing frequency selective CSI achieves an average positioning error of 60cm, outperforming methods that process received signal strength information only. The mean localization accuracy loss compared to a non-scalable approach with perfect synchronization and CSI is 20cm.

AlkuperäiskieliEnglanti
Otsikko2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication, SPAWC 2022
KustantajaIEEE
Sivumäärä5
ISBN (elektroninen)978-1-6654-9455-7
DOI - pysyväislinkit
TilaJulkaistu - 2022
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE International Workshop on Signal Processing Advances in Wireless Communication - Oulu, Suomi
Kesto: 4 heinäk. 20226 heinäk. 2022

Julkaisusarja

NimiSPAWC
Vuosikerta2022-July
ISSN (elektroninen)1948-3252

Conference

ConferenceIEEE International Workshop on Signal Processing Advances in Wireless Communication
LyhennettäSPAWC
Maa/AlueSuomi
KaupunkiOulu
Ajanjakso04/07/202206/07/2022

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