A Kalman-filter based paging strategy for cellular networks

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dc.contributor.author Tung, TT
dc.contributor.author Jamalipour, A
dc.contributor.editor Sprague, R
dc.date.accessioned 2010-07-13T08:50:02Z
dc.date.issued 2003-01
dc.identifier.citation 36th Annual Hawaii international Conference on System Sciences, 2003, pp. 1 - 10
dc.identifier.isbn 0-7695-1874-5
dc.identifier.other E1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/12614
dc.description.abstract Developing an efficient location management technique isan important step in working towards the determinationof an optimal solution to the problem of managingmobility. Given the irregular nature of cell sizes in acellular network, the behavior of mobile movementchanges from cell to cell and from user to user. Thus, theneed for designing an adaptive algorithm for tracking aroaming mobile becomes imperative. In this paper, wepropose a new predictive location management strategythat reduces the update cost while restricting the pagingload optimized for mobiles roaming with traceablepatterns. Enhanced with directional predictivecapabilities offered by Kalman filtering, new updateboundaries are assigned to better reflect the movementpatterns of individual mobiles upon location registration.Thus, while complying with the required delayconstraints, QoS measures (mainly throughput) will notneed to be sacrificed as a result of increasing the updatethreshold. The contribution of this paper is two-fold: (1)to suggest a distribution model that is capable ofdescribing a wide range of movement patterns withvarying correlation between traveling directions and (2)to explore the capabilities in terms of reliableperformances of Kalman filter in predicting futuremovement patterns. Simulation results have successfullydemonstrated the ability of Kalman filter in assigningupdate boundaries capable of reflecting a mobile'sroaming characteristics. The performance gains,achieved mainly through a significant reduction in thenumber of updates, indicate its potential for promotingbetter bandwidth conservation
dc.publisher IEEE Computer Society
dc.title A Kalman-filter based paging strategy for cellular networks
dc.type Conference Proceeding
dc.parent 36th Annual Hawaii international Conference on System Sciences
dc.journal.number en_US
dc.publocation USA en_US
dc.identifier.startpage 1 en_US
dc.identifier.endpage 10 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.conference Hawaii International Conference on System Sciences
dc.for 0806 Information Systems
dc.personcode 040175
dc.percentage 100 en_US
dc.classification.name Information Systems en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom Hawaii International Conference on System Sciences en_US
dc.date.activity 20030106 en_US
dc.date.activity 2003-01-06
dc.location.activity Hawaii en_US
dc.description.keywords en_US
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computing and Communications
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history School of Computing and Communications (ID: 335)
utslib.collection.history Closed (ID: 3)


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