In a multisystem environment where a mobile node can utilize multiple interfaces and simultaneously connect to multiple providers, new opportunities exist for efficient location management strategies spanning heterogeneous cellular wireless networks. In this paper, an integrated framework is developed for location management in such a multi-system, fourth generation (4 G) wireless networks. This information-theoretic framework allows each individual sub-system to operate fairly independently, and does not require the knowledge of individual sub-network topologies. An efficient location management in such a loosely coupled network is designed by having a mobile node view its movement as a vector-valued sequence, and then transmit this sequence in an entropy coded form to the network. We demonstrate how an intelligent, integrated paging strategy must consider the joint residence probability distribution of a mobile node in multiple sub-networks. We prove that the determination of an optimal paging sequence is NP-complete, and also propose an efficient greedy heuristic to compute the paging sequence, both without and with bounds on the paging delay. Three different location tracking strategies are proposed and evaluated; they differ in their degrees of centralized control and provide tradeoff between the location 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, multi-system location management strategy.
LZ compression, Location management, paging, multi-system, cellular networks, information theory
Software and Cyber-Physical Systems
IEEE/ACM Transactions on Networking
MISRA, Archan; ROY, Abhishek; and DAS, Sajal K..
Information-Theory Based Optimal Location Management Schemes for Integrated Multi-System Wireless Networks. (2008). IEEE/ACM Transactions on Networking. 16, (3), 525-538. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/656
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