Paper Info
Title
An experimental study of indoor RSS-based RF fingerprinting localization using GSM and Wi-Fi signals
Abstract
Localization of mobile users in indoor environments has many practical applications in daily life. In this paper, we study the performance of the received signal strength (RSS)-based radio frequency (RF) fingerprinting localization method in a shopping mall environment considering both calibration and practical measurement cases. In the calibration case, the test data for the RSS fingerprinting database are built offline by receiving signals from Global System for Mobile Communications (GSM) base stations, which are collected by a dedicated measurement tool, i.e. the Test Mobile System. In order to see the localization performance, the k-nearest neighbors (K-NN) and random decision forest (RDF) algorithms are implemented. The RDF algorithm provides a better localization performance than K-NN in this case. For the practical implementations, the RSS values of both GSM and Wi-Fi signals are collected by ordinary smartphones. Localization is performed using different classification algorithms, i.e. BayesNet, support vector machines, K-NN, RDF, and J48. Moreover, the effects of the received signal type, phone type, and number of reference points on localization performance are investigated.
Year
DOI
Venue
2017
10.3906/elk-1601-94
TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
Keywords
DocType
Volume
Indoor localization,radio frequency fingerprinting,received signal strength,Wi-Fi,Global System for Mobile Communications
Journal
25
Issue
ISSN
Citations 
4.0
1300-0632
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Gökhan Çelik111.03
Hasari Celebi28913.00
Hakan P. Partal300.68
Engin Zeydan416031.05
Ilyas Alper Karatepe5302.20
Ahmet Salih Er600.34