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Localization of eNodeBs with a Large Set of Measurements from Train Routers
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Lokalisering av eNodeB:er med en stor mängd mätningar från tåg routrar (Swedish)
Abstract [en]

This master thesis investigates the possibility of locating LTE base stations, known as eNodeBs, using signal measurements collected by routers on trains. Four existing algorithms for transmitter localization are adopted: the centroid, strongest signal, Monte Carlo path loss simulation and power difference of arrival (PDoA) methods. An improved version of Monte Carlo path loss simulation called logloss fitting is proposed. Furthermore, a novel localization method called sector fitting is presented, which operates solely on the cell identity and geographical distribution of the measurements.

The methods are evaluated for a set of manually located eNodeBs, and the results are compared to other external systems that can be used to locate eNodeBs. It is found that the novel sector fitting algorithm is able to considerably improve the accuracy of the logloss fitting and PDoA methods, but weighted centroid is overall the most accurate of the considered methods, providing a median error of approximately 1 km. The Google Geolocation API and Mozilla Location Service still provides estimates that are generally closer to the true location than any of the considered methods. However, for a subset of eNodeBs where measurements from all sectors are available, the novel sector fitting algorithm combined with logloss fitting outperforms the external systems. Therefore, a hybrid approach is suggested, where sector fitting combined with logloss fitting or weighted centroid is used to locate eNodeBs that have measurements from all sectors, while Google Geolocation API or Mozilla Location Service is used to locate the remaining eNodeBs.

It is concluded that while the localization performance for those eNodeBs that have measurements from all sectors is relatively good, further improvements to the overall results can likely be obtained in future work by considering environmental factors, the angular losses introduced by directional antennas, and the effects of downlink power control.

Place, publisher, year, edition, pages
2019. , p. 92
Keywords [en]
Localization, Positioning, LTE, eNodeB, base stations, Received Signal Strength, RSS
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kau:diva-75456OAI: oai:DiVA.org:kau-75456DiVA, id: diva2:1365990
External cooperation
Icomera AB
Subject / course
Computer Science
Educational program
Engineering: Computer Engineering (300 ECTS credits)
Presentation
2019-06-13, 21E 415A, Universitetsgatan 2, Karlstad, 13:00 (English)
Supervisors
Examiners
Available from: 2019-11-21 Created: 2019-10-27 Last updated: 2019-11-21Bibliographically approved

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