Robust extended Kalman filter based technique for location management in PCS networks

Pathirana, Pubudu, Savkin, Andrey and Jha, Sanjay 2004, Robust extended Kalman filter based technique for location management in PCS networks, Computer communications, vol. 27, no. 5, pp. 502-512.

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Title Robust extended Kalman filter based technique for location management in PCS networks
Author(s) Pathirana, Pubudu
Savkin, Andrey
Jha, Sanjay
Journal name Computer communications
Volume number 27
Issue number 5
Start page 502
End page 512
Publisher Elsevier Science Pub.
Place of publication New York, NY
Publication date 2004-03-20
ISSN 0140-3664
1873-703X
Keyword(s) location tracking
mobility modelling
robust extended Kalman filter
personal communications service networks
Summary Provisioning 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 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. Through simulation, we show the accuracy and simplicity in implementation of our prediction algorithm.
Notes Available online 5 November 2003
Language eng
Field of Research 100503 Computer Communications Networks
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ┬ęCopyright 2003 Elsevier B.V.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30002354

Document type: Journal Article
Collection: School of Information Technology
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