A Kalman-filter based paging strategy for cellular networks

IEEE Computer Society
Publication Type:
Conference Proceeding
36th Annual Hawaii international Conference on System Sciences, 2003, pp. 1 - 10
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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
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