Efficient location area planning for cellular networks with hierarchical location databases

Authors:
Shi-Wu Lo;Tei-Wei Kuo;Kam-Yiu Lam;Guo-Hui Li
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan, ROC;Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan, ROC;Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, PR China;School of Computer Science and Technology, Huazhong University of Science & Technology, Wuhan, Hubei, PR China
Venue:
Computer Networks: The International Journal of Computer and Telecommunications Networking
Year:
2004

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Abstract

Location area planning (LAP) is an important issue in the design of high-performance PCS networks. It could have a serious impact on the total mobility management cost of mobile terminals. Most of the previous works either explored the LAP problem as a 0-1 linear programming problem or used adopted techniques, such as simulated annealing, taboo search, and genetic algorithms [IEEE Trans. Vehicular Technol. 49 (2000) 1678; Proceedings of 1999 Vehicular Technology Conference, vol. 4, 1999, pp. 2119-2123; IEEE Vehicular Technol. Conf. 3 (1996) 1835; Proceedings of IEEE INFOCOM'01, Anchorage, Alaska, April 2001; IEEE Trans. Vehicular Technol. 47 (1998) 987], to derive a solution to minimize the location update cost. In this paper, we model and resolve the LAP problem as a set-covering problem. The main advantage of this approach is that it can adapt to the changing mobility patterns of the mobile terminals. We propose the set-covering-based location area planning (SCBLP) algorithm to minimize the total number of location updates, in which the cost-benefit functions are defined based on the coupling and cohesive functions among neighboring cells. We then apply SCBLP to the location database system with a hierarchical structure to further improve the overall system performance in searching and updating the location databases. Extensive simulation experiments have been conducted, and the experimental results show that our proposed algorithms can significantly reduce the location management costs, compared to the greedy algorithm and the random algorithm.