A dynamic location tracking strategy for mobile communication systems

We present a dynamic predictive location management scheme using a continuous-time Markovian mobility model characterized by cell-to-cell transition probabilities. The size and shape of location areas (LAs) are determined dynamically and individually for each mobile user on the basis of gathered statistics and incoming call patterns. In this way, the combined average cost of location updating and paging signaling for each individual mobile user is reduced. In addition, we develop an algorithm to compute the probabilities of finding a mobile user in each cell of its current LA. An optimal multi-step paging algorithm is used to minimize the paging signaling cost. The numerical results demonstrate that the proposed scheme can significantly reduce combined location updating and paging signaling cost