Paging strategy optimization in personal communication systems
Wireless Networks
Minimizing the average cost of paging under delay constraints
Wireless Networks
LeZi-update: an information-theoretic approach to track mobile users in PCS networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Introduction to 3G Mobile Communications
Introduction to 3G Mobile Communications
Efficient Location and Paging Area Planning in Future Cellular Systems
Wireless Personal Communications: An International Journal
A Kalman-Filter Based Paging Strategy for Cellular Networks
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 9 - Volume 9
Design and Analysis of Location Management for 3G Cellular Networks
IEEE Transactions on Parallel and Distributed Systems
The predictive user mobility profile framework for wireless multimedia networks
IEEE/ACM Transactions on Networking (TON)
Mobility modeling, location tracking, and trajectory prediction in wireless ATM networks
IEEE Journal on Selected Areas in Communications
Serving radio network controller relocation for UMTS all-IP network
IEEE Journal on Selected Areas in Communications
Paging mobile users in cellular networks: Optimality versus complexity and simplicity
Theoretical Computer Science
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Location tracking is one of the most important issues in providing real-time applications over wireless networks due to its effect to quality of service (QoS), such as end-to-end delay, bandwidth utilization, and connection dropping probability. In this paper, we study cost minimization for locating mobile users under delay constraints in mobile wireless networks. Specifically, a new location tracking algorithm is developed to determine the position of mobile terminals under delay constraints, while minimizing the average locating cost based on a unimodal property. We demonstrate that the new algorithm not only results in minimum locating cost, but also has a lower computational complexity compared to existing algorithms. Furthermore, detailed searching procedures are discussed under both deterministic and statistic delay bounds. Numerical results for a variety of location probability distributions show that our algorithm compares favorably with existing algorithms.