An information-theoretic framework for optimal location tracking in multi-system 4G wireless networks

An information-theoretic framework is developed for optimal location management in multi-system, fourth generation (4G) wireless networks. The framework envisions that each individual sub-system operates fairly independently, and does not require public knowledge of individual sub-network topologies. To capture the variation in paging and location update costs in this heterogeneous environment, the location management problem is formulated in terms of a new concept of weighted entropy. The update process is based on the Lempel-Ziv compression algorithms, which are applied to a vector-valued sequence consisting of both the mobile's movement pattern and its session activity state. Three different tracking strategies which differ in their degrees of centralized control and provide trade off between the location update and paging costs, are proposed and evaluated. While both the proposed centralized and distributed location management strategies are endowed with optimal update capability, the proposed selective location management heuristic also offers a practical trade off between update and paging costs. Simulation experiments demonstrate that our proposed schemes can result in more than 50% savings in both update and paging costs, in comparison with the basic movement-based, multisystem location management strategy. These update strategies can he realized with only modest amounts of memory (12-15 Kbytes) on the mobile.