RF fingerprinting for user locationing in LTE/WLAN networks

Abstract

Location based applications and services have become popular in many wireless communication devices. This thesis study presents a performance evaluation of Radio Frequency (RF) fingerprinting framework in heterogeneous Long Term Evolution (LTE) and Wireless Local Area Networks (WLAN) using Minimization of Drive Testing (MDT) measurements which allow automated construction of extensive RF fingerprint training databases. Utilization of MDT data could create additional opportunities for service provider and application developers. Typical RF fingerprint consist of radio measurements from multiple LTE transceiver stations and WLAN access points. Regardless environmental conditions, received signal strength indicator pattern for difference reference points, set a fingerprint of radio conditions for the specific location. Based on RF fingerprinting framework for positioning by using MDT measurements specified in LTE release 10, performance of locating user equipment was studied by signal strength mean value algorithm using grid based method at outdoor environment. To find out the optimal grid size, three different grid size were used. Source of positioning error and effects have been extensively investigated. Cumulative distribution function has been used to express the result. This study suggests that, MDT based RF fingerprint locationing system can provide a good basis for the network based proximity detection.