Practical considerations for RSS RF fingerprinting based indoor localization systems

Author

Bacak, Ahmet ; Celebi, Haluk

Author_Institution

Bilgisayar Muhendisligi Bolumu, Gebze Yuksek Teknoloji Enstitusu, Gebze, Turkey

fYear

2014

fDate

23-25 April 2014

Firstpage

497

Lastpage

500

Abstract

There are different location estimation approaches in order to determine the position of a mobile users precisely in indoor environments. In this study, in order to determine the position of the mobile user at the shopping malls received signal strength (RSS) RF fingerprint based approaches is considered. Wi-Fi and GSM RSS data has been collected by using LG Nexus 4 cell phone at Gebze Center shopping mall in Gebze, Kocaeli. By using the collected data, the effects of different machine learning algorithms, number of training data, number of measurement grid, and signal type on the performance of the localization systems are studied. According to the results, it is observed that, combining Wi-Fi and GSM RSS data measurements decreases the location estimation error.

Keywords

cellular radio; indoor radio; learning (artificial intelligence); mobile radio; wireless LAN; GSM; Gebze Center shopping mall; Kocaeli; LG Nexus 4 cell phone; RF fingerprinting; RSS; Wi-Fi; indoor localization systems; location estimation; machine learning algorithms; mobile users; received signal strength; shopping malls; Conferences; GSM; Global Positioning System; IEEE 802.11 Standards; Radio frequency; Signal processing; Support vector machines; indoor localization; rf fingerprinting; the estimation of mobile user;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications Applications Conference (SIU), 2014 22nd

Conference_Location

Trabzon

Type

conf

DOI

10.1109/SIU.2014.6830274

Filename

6830274