Outdoor Positioning Algorithms Based on LTE and WiFi Measurements

This scientific work focuses on outdoor positioning in WLAN and 4G wireless cellular networks based on extensive collection of radio measurements from WiFi and LTE signals, supplied with Global Positioning System location information and time stamp. The objective of work is to explore the performance of different RSS-based outdoor positioning algorithms in terms of distance error and database. The objective includes, through simulating experiments, to verify if accuracy is in compliance with the E911 requirements. The scope of the research is to establish an energy-efficient and low-latency solution for accurate and reliable outdoor positioning based on cellular networks. Two probabilistic models based on coverage-area and path-loss are studied and implemented whereas the more common deterministic model based on classical-fingerprinting is used as benchmark for assessing the performance. The advantage of using probabilistic model over deterministic is that only few parameters per transmitter identification need to be stored and hence there is a significant reduction of the database size. Results show that statistical models suffer accuracy loss to some extent but nevertheless, the decrease in accuracy is not significant with respect to the requirements imposed by FCC