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Location estimation and trajectory prediction for cellular networks with mobile base stations
journal contribution
posted on 2004-11-01, 00:00 authored by Pubudu PathiranaPubudu Pathirana, A Savkin, S JhaLocation estimation and trajectory prediction for cellular networks with mobile base stations
History
Journal
IEEE transactions on vehicular technologyVolume
53Issue
6Pagination
1903 - 1913Publisher
Institute of Electrical and Electronics EngineersLocation
New York, N.Y.ISSN
0018-9545eISSN
1939-9359Language
engNotes
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.Publication classification
C1 Refereed article in a scholarly journalCopyright notice
2004, IEEEUsage metrics
Categories
No categories selectedKeywords
ad hoc networksCarNetlocation trackingmobility modelingrobust extended Kalman filterScience & TechnologyTechnologyEngineering, Electrical & ElectronicTelecommunicationsTransportation Science & TechnologyEngineeringTransportationrobust extended Kalman filter (REKF)H-INFINITY CONTROLUNCERTAIN SYSTEMSSTATE ESTIMATIONTRACKING
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