Enhancements in LTE OTDOA Positioning for Multipath Environments
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Förbättringar i LTE OTDOA-positionering för multipath-miljöer (Swedish)
By using existing radio network infrastructure, a user can be positioned even where GPS and other positioning technologies lack coverage. The LTE Positioning Protocol (LPP) supports user Reference Signal Time Difference (RSTD) reports based on the Time of Arrival (TOA) for a Positioning Reference Signal (PRS). In the current reporting format, only one RSTD for each base station is considered, but for indoor environments this is easily biased due to fading and multipath issues, resulting in a Non-Line of Sight (NLOS) bias. With a rich User Equipment (UE) feedback that can represent the multipath channel for each Base Station (BS), the positioning accuracy can be increased. This thesis develops and evaluates a UE reporting format representing multiple TDOA candidates, and a probabilistic positioning algorithm, in terms of positioning accuracy and amount of data reported. By modeling time measurements as Gaussian Mixture (GM), the time information can be compressed with arbitrary resolution and used in a Maximum-Likelihood (ML) estimation to find the position. Results were obtained through simulation in a radio network simulator and post-processing of simulation data in Matlab. The results suggest that several TOA candidates improve the positioning accuracy, but that the largest improvement comes from a noise based threshold by increasing LOS detectability reducing the NLOS bias, while suppressing noise. The results also suggest that the accuracy for the method can be further improved by combining multiple time measurement occasions.
Place, publisher, year, edition, pages
2016. , 62 p.
positioning, TDOA, NLOS bias, multiple TOA candidates, probabilistic method, ML estimation, LTE, simulation
IdentifiersURN: urn:nbn:se:liu:diva-131821ISRN: LiTH-ISY-EX--16/4950--SEOAI: oai:DiVA.org:liu-131821DiVA: diva2:1033724
Subject / course
2016-08-17, Linköping, 13:15 (English)
Savic, VladimirRyden, HenrikRazavi, Sara Modarres