Localization using radial basis function networks and signal strength fingerprints in WLAN

Christos Laoudias; Paul Kemppi; G. Panayiotou Christos

doi:10.1109/GLOCOM.2009.5425278

Localization using radial basis function networks and signal strength fingerprints in WLAN

Christos Laoudias, Paul Kemppi, G. Panayiotou Christos

University of Cyprus

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

66 Citations (Scopus)

Abstract

Fingerprinting localization techniques provide reliable location estimates and enable the development of location aware applications especially for indoor environments, where satellite based positioning is infeasible. In our approach we utilize Received Signal Strength (RSS) fingerprints collected in known locations and employ a Radial Basis Function (RBF) neural network to approximate the function that maps fingerprints to location coordinates. We present a clustering scheme to reduce the size and computational complexity of the RBF architecture and demonstrate the applicability of this approach in a real-world WLAN setup. Experimental results indicate that the RBF based method is an efficient approach to the location determination problem that outperforms existing techniques in terms of the positioning error.

Original language	English
Title of host publication	Proceedings of GLOBECOM 2009
Subtitle of host publication	2009 IEEE Global Telecommunications Conference
Publisher	IEEE Institute of Electrical and Electronic Engineers
Number of pages	6
ISBN (Print)	978-1-4244-4148-8
DOIs	https://doi.org/10.1109/GLOCOM.2009.5425278
Publication status	Published - 2009
MoE publication type	A4 Article in a conference publication
Event	IEEE Global Telecommunications Conference, GLOBECOM 2009 - Honolulu, United States Duration: 30 Nov 2009 → 4 Dec 2009

Conference

Conference	IEEE Global Telecommunications Conference, GLOBECOM 2009
Abbreviated title	GLOBECOM 2009
Country/Territory	United States
City	Honolulu
Period	30/11/09 → 4/12/09

Keywords

fingerprinting
localization
Radial Basis Function Networks
received signal strength
WLAN

Access to Document

10.1109/GLOCOM.2009.5425278

Cite this

@inproceedings{aa4ed781e54b4e4db49d1ed601985795,

title = "Localization using radial basis function networks and signal strength fingerprints in WLAN",

abstract = "Fingerprinting localization techniques provide reliable location estimates and enable the development of location aware applications especially for indoor environments, where satellite based positioning is infeasible. In our approach we utilize Received Signal Strength (RSS) fingerprints collected in known locations and employ a Radial Basis Function (RBF) neural network to approximate the function that maps fingerprints to location coordinates. We present a clustering scheme to reduce the size and computational complexity of the RBF architecture and demonstrate the applicability of this approach in a real-world WLAN setup. Experimental results indicate that the RBF based method is an efficient approach to the location determination problem that outperforms existing techniques in terms of the positioning error.",

keywords = "fingerprinting, localization, Radial Basis Function Networks, received signal strength, WLAN",

author = "Christos Laoudias and Paul Kemppi and {Panayiotou Christos}, G.",

year = "2009",

doi = "10.1109/GLOCOM.2009.5425278",

language = "English",

isbn = "978-1-4244-4148-8",

booktitle = "Proceedings of GLOBECOM 2009",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

address = "United States",

note = "IEEE Global Telecommunications Conference, GLOBECOM 2009, GLOBECOM 2009 ; Conference date: 30-11-2009 Through 04-12-2009",

}

Laoudias, C, Kemppi, P & Panayiotou Christos, G 2009, Localization using radial basis function networks and signal strength fingerprints in WLAN. in Proceedings of GLOBECOM 2009: 2009 IEEE Global Telecommunications Conference. IEEE Institute of Electrical and Electronic Engineers, IEEE Global Telecommunications Conference, GLOBECOM 2009, Honolulu, Hawaii, United States, 30/11/09. https://doi.org/10.1109/GLOCOM.2009.5425278

Localization using radial basis function networks and signal strength fingerprints in WLAN. / Laoudias, Christos; Kemppi, Paul; Panayiotou Christos, G.
Proceedings of GLOBECOM 2009: 2009 IEEE Global Telecommunications Conference. IEEE Institute of Electrical and Electronic Engineers, 2009.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Localization using radial basis function networks and signal strength fingerprints in WLAN

AU - Laoudias, Christos

AU - Kemppi, Paul

AU - Panayiotou Christos, G.

PY - 2009

Y1 - 2009

N2 - Fingerprinting localization techniques provide reliable location estimates and enable the development of location aware applications especially for indoor environments, where satellite based positioning is infeasible. In our approach we utilize Received Signal Strength (RSS) fingerprints collected in known locations and employ a Radial Basis Function (RBF) neural network to approximate the function that maps fingerprints to location coordinates. We present a clustering scheme to reduce the size and computational complexity of the RBF architecture and demonstrate the applicability of this approach in a real-world WLAN setup. Experimental results indicate that the RBF based method is an efficient approach to the location determination problem that outperforms existing techniques in terms of the positioning error.

AB - Fingerprinting localization techniques provide reliable location estimates and enable the development of location aware applications especially for indoor environments, where satellite based positioning is infeasible. In our approach we utilize Received Signal Strength (RSS) fingerprints collected in known locations and employ a Radial Basis Function (RBF) neural network to approximate the function that maps fingerprints to location coordinates. We present a clustering scheme to reduce the size and computational complexity of the RBF architecture and demonstrate the applicability of this approach in a real-world WLAN setup. Experimental results indicate that the RBF based method is an efficient approach to the location determination problem that outperforms existing techniques in terms of the positioning error.

KW - fingerprinting

KW - localization

KW - Radial Basis Function Networks

KW - received signal strength

KW - WLAN

U2 - 10.1109/GLOCOM.2009.5425278

DO - 10.1109/GLOCOM.2009.5425278

M3 - Conference article in proceedings

SN - 978-1-4244-4148-8

BT - Proceedings of GLOBECOM 2009

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - IEEE Global Telecommunications Conference, GLOBECOM 2009

Y2 - 30 November 2009 through 4 December 2009

ER -