Mobility Pattern Learning and Route Prediction Based Location Management in PCS Network

Abstract

Mobile host (MH) has to be tracked in personal communication service (PCS) network, for which update and paging signals are required. The number of PCS network subscribers skyrocketed in recent years. To reuse channels over a distance, cell size is reduced and the number of cell crossing by user is becoming high. That makes optimal use of paging and update signal very important. In fact, most MH has unique movement profile, that contains the information of time, route, direction, etc., which is possible to learn and used to predict location. In this paper, we propose mobility pattern based location management scheme using the movement profile. Mobility pattern is learned and system will page only the restricted probable area. We compared the proposed scheme with distance-based location management. Improved cost saving is achieved.

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