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Robust extended kalman filter applied to location tracking and trajectory prediction for PCS networks
conference contribution
posted on 2004-01-01, 00:00 authored by Pubudu PathiranaPubudu Pathirana, A Savkin, S JhaProvisioning of real-time multimedia sessions over wireless cellular network poses unique challenges due to frequent handoff and rerouting of a connection. For this reason, the wireless networks with cellular architecture require efficient user mobility estimation and prediction. This paper proposes using robust extended Kalman filter (REKF) as a location heading altitude estimator of mobile user for next cell prediction in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm reduces the system complexity (compared to existing approach using pattern matching and Kalman filter) as it requires only two base station measurements or only the measurement from the closest base station. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model and more effective in comparison with the standard Kalman filter.
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Title of proceedings
Proceedings of 2004 IEEE Conference on Control Applications : September 2-4, 2004, the Grand Hotel, Taipei, TaiwanEvent
IEEE International Conference on Control Applications (2004 : Taipei, Taiwan)Pagination
63 - 68Publisher
IEEELocation
Taipei, TaiwanPlace of publication
Piscataway, N.J.Start date
2004-09-02End date
2004-09-04ISBN-13
9780780386341ISBN-10
0780386337Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2004, IEEEEditor/Contributor(s)
F Li-ChenUsage metrics
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