DocumentCode :
2762104
Title :
Indoor location using received signal strength of IEEE 802.11b access point
Author :
Wassi, Gilles Ibrahim ; Despins, Charles ; Grenier, Dominic ; Nerguizian, Chahé
Author_Institution :
Fac. des Sci. et de Genie, Laval Univ., Que.
fYear :
2005
fDate :
1-4 May 2005
Firstpage :
1367
Lastpage :
1370
Abstract :
In this paper, the fingerprinting technique is employed to locate a mobile user inside a building. The fingerprint information, collected from real in-building measurements, is formed by three IEEE 802.11b access points´ signal strength data received by the mobile user. Three different pattern-matching algorithms have been studied: the multi-layer perceptron (MLP) neural network, the generalized radial neural network (GRNN) and the K-nearest neighbours (KNN) algorithm. Their performances in terms of localization accuracy are compared on both training and testing data. Results show that the K-nearest neighbours gives the best localization accuracy. The effect of the measurement´s grid spacing has also been investigated. Experimental results show that the localization accuracy increases when the grid spacing decreases. However, when the spacing reaches a certain threshold value, the accuracy starts to deteriorate. It can be shown that, in reality, the localization accuracy is improved even after the considered threshold value
Keywords :
indoor radio; multilayer perceptrons; pattern matching; wireless LAN; IEEE 802.11b access point; K-nearest neighbours; fingerprinting technique; generalized radial neural network; indoor location; multilayer perceptron neural network; pattern-matching algorithms; received signal strength; Base stations; Databases; Fingerprint recognition; Mathematical model; Multi-layer neural network; Multilayer perceptrons; Neural networks; Pattern matching; Performance evaluation; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering, 2005. Canadian Conference on
Conference_Location :
Saskatoon, Sask.
ISSN :
0840-7789
Print_ISBN :
0-7803-8885-2
Type :
conf
DOI :
10.1109/CCECE.2005.1557232
Filename :
1557232
Link To Document :
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