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A Low-cost Fingerprint Positioning System in

A Low-cost Fingerprint Positioning System in - A Low-cost...

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A Low-cost Fingerprint Positioning System in Cellular Networks Claude Takenga Institute of communications engineering Leibniz University of Hannover Appelstrasse 9A, 30167 Hannover, Germany [email protected] Abstract - An ultimate aim of mobile positioning research is to find a method providing high estimation accuracy to the user within minimum delay and at minimum cost. Conventional location techniques based on trilateration and triangulation rely on line-of-sight path between the base station antenna and the mobile unit. In densely built urban areas, this assumption is rarely valid. This fact degrades the location performance of the conventional techniques and motivates the need for development of more accurate technique suited for these areas. Positioning system developed in this research is divided into three sub-systems. The first sub-system solves the problems related to fingerprint localization and involves neural network as key element of the positioning algorithm. The post- processing tasks which include tracking and map-matching are performed in the second and third sub-systems respectively. Keywords - Fingerprint Positioning, Mobile Localization, Kalman Filter, Map-Matching, Neural Networks. I. INTRODUCTION Mobile localization techniques have been under strong development during the last years. There is a broad agreement that localization will play a central role in enabling value-added services in the new generation cellular networks and that these services require high accuracy at low cost. The Global Positioning System (GPS) is a popular solution for providing location in terrestrial wireless communication networks. GPS is a proven technology and provides high accuracy when a line-of-sight (LOS) path exists between the receiver and at least four satellites. However, GPS is often inoperable in areas where satellites are blocked, such as in buildings and built-up urban areas. Much of the activities in the area of wireless positioning have been driven by the 1996 Report and order of the Federal Communications Commission (FCC) [1]. Since then, different positioning systems working within a cellular network have been developed [2-4]. Parameters that are often measured and used for location include received signal strength (RSS), angle-of-arrival (AoA), time-of- arrival (ToA) and time differences of arrival (TDoA). Direction finding and ranging methods perform well in environment characterised with LOS. In dense urban area, additional algorithms should be added which deal with non- line-of-sight (NLOS). Moreover, these methods require additional equipment for their implementations (directional antennas at every base station (BS) for AoA and very accurate clock for ranging methods). Kyandoghere Kyamakya Department of Smart System Technologies Alpen Adria University Klagenfurt Klagenfurt, Austria [email protected] Fingerprint localization methods perform relatively better in urban area compared to other methods. Moreover, this approach does not require any additional equipment for its
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