Optimum Mirror-HLR Locations to Reduce Signalling Load in Cellular Radio Networks

  • Rudolf Mathar
  • Martin Hellebrandt


As a new policy, Mirror Home Location Registers (MHLR) are introduced to avoid expensive signalling traffic of roaming users to a far distant HLR in mobile communication networks. We investigate the question what the optimum location strategy will be. Three basic ingredients are necessary to tackle this problem: a realistic, but tractable, mobility model, a precise description of signalling costs, and an optimization method to solve the complicated minimization problems.

This paper contributes to each of these problems in the following way. An open Jackson network with customer classes is developed to describe user mobility and network flows. Then, a careful analysis of the signalling messages yields an accurate cost function. Finally, in steady state of the network, integer linear programming is used to find an optimal register allocation strategy for the so called dedicated MHLR policy, where each location area is assigned to an individual MHLR. Numerical examples show that the optimum Mirror HLR strategy clearly outperforms standard GSM signalling protocols.


User Mobility Integer Linear Programming Arrival Intensity Visitor Location Register Customer Class 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. [1]
    J. Wang, “A Fully Distributed Location Registration Strategy for Universal Personal Communication Systems,” IEEE Journal on Selected Areas in Communications, vol. 11, pp. 850–860, Aug. 1993.CrossRefGoogle Scholar
  2. [2]
    V. Anantharam, M. Honig, U. Madhow, and V. Wei, “Optimization of a database hierarchy for mobility tracking in a personal communications network,” Performance Evaluation, vol. 20, pp. 287–300, 1994.CrossRefGoogle Scholar
  3. [3]
    R. Jain and Y. Lin, “An auxiliary user location strategy employing forwarding pointers to reduce network impacts of PCS,” Wireless Networks, pp. 197–210, 1995.Google Scholar
  4. [4]
    R. Jain, Y.-B. Lin, and S. Mohan, “A caching strategy to reduce network impacts of PCS,” IEEE Journal on Selected Areas in Communications, vol. 12, pp. 1434–1444, Oct. 1994.CrossRefGoogle Scholar
  5. [5]
    J. Ho and I. Akyildiz, “Local anchor scheme for reducing signaling costs in personal communications networks,” IEEE/ACM Transactions on Networking, vol. 4, pp. 709–725, Oct. 1996.CrossRefGoogle Scholar
  6. [6]
    A. Bondi and V. Jin, “Performance analysis of a minimally replicated database for UPT services,” in Proceedings 8th ITC Specialists Seminar on UPT, pp. 131–140, Oct. 1992.Google Scholar
  7. [7]
    K. Leung and Y. Levy, “Use of centralized and replicated databases for global mobility management in PCN,” in Proceedings of ICUPC’96, pp. 852–859, Oct. 1996.Google Scholar
  8. [8]
    G. Colombo, “Mobility models for mobile systems design and analysis,” in Proceedings 9th ITC Specialists Seminar, pp. 133–146, KPN Research, Leidschen-dam, 1995.Google Scholar
  9. [9]
    R. Wolff, Stochastic Modeling and the Theory of Queues. Englewood Cliffs: Prentice-Hall, 1989.zbMATHGoogle Scholar
  10. [10]
    M. Hellebrandt and R. Mathar, “Mobility and traffic modeling for optimum system design of cellular radio networks,” submitted for publication, 1997.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1998

Authors and Affiliations

  • Rudolf Mathar
    • 1
  • Martin Hellebrandt
    • 1
  1. 1.Aachen University of TechnologyAachenGermany

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