Location estimation and trajectory prediction for cellular networks with mobile base stations Pathirana, Pubudu, Savkin, Andrey and Jha, Sanjay 2004, Location estimation and trajectory prediction for cellular networks with mobile base stations, IEEE transactions on vehicular technology, vol. 53, no. 6, pp. 1903-1913. Attached Files Name Description MIMEType Size Downloads Title Location estimation and trajectory prediction for cellular networks with mobile base stations Author(s) Pathirana, Pubudu orcid.org/0000-0001-8014-7798 Savkin, Andrey Jha, Sanjay Journal name IEEE transactions on vehicular technology Volume number 53 Issue number 6 Start page 1903 End page 1913 Publisher Institute of Electrical and Electronics Engineers Place of publication New York, N.Y. Publication date 2004-11 ISSN 0018-9545 1939-9359 Keyword(s) ad hoc networks CarNet location tracking mobility modeling robust extended Kalman filter Notes This paper provides mobility estimation and prediction for a variant of the GSM network that resembles an ad hoc wireless mobile network in which base stations and users are both mobile. We propose using a Robust Extended Kalman Filter (REKF) to derive an estimate of the mobile user's next mobile base station from the user's location, heading, and altitude, to improve connection reliability and bandwidth efficiency of the underlying system. Our analysis demonstrates that our algorithm can successfully track the mobile users with less system complexity, as it requires measurements from only one or two closest mobile base stations. Further, the technique is robust against system uncertainties caused by the inherent deterministic nature of the mobility model. Through simulation, we show the accuracy of our prediction algorithm and the simplicity of its implementation. Language eng Field of Research 100503 Computer Communications Networks HERDC Research category C1 Refereed article in a scholarly journal Copyright notice ©2004, IEEE Persistent URL http://hdl.handle.net/10536/DRO/DU:30002586 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment School of Engineering and Technology Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Fri, 13 Jun 2014, 22:33:36 EST Wed, 21 Oct 2015, 16:20:25 EST Tue, 06 Sep 2016, 08:56:59 EST Filtered Full Citation counts:   Cited 63 times in TR Web of Science Cited 74 times in Scopus Search Google Scholar Access Statistics: 875 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Mon, 07 Jul 2008, 08:28:53 EST

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