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Application of renewal theory to call handover counting and dynamic location management in cellular mobile networks

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  • Rodríguez-Dagnino, Ramón M.
  • Takagi, Hideaki

Abstract

Mobility management in wireless cellular networks is one of the main issues for resource optimization. It is aimed to keep track of Mobile Stations (MSs) in the different Location Areas (LAs) or Registration Areas (RAs) for an efficient call delivery. The optimization issues of these location strategies look for a minimization of the generated signaling traffic. We describe the three basic strategies for location management: distance-based, time-based and movement-based, and their corresponding optimization cost. We emphasize that counting the number of wireless cell crossings or handovers occurring in the call duration time or during inter-call times is a fundamental issue for mobility management analysis. We present the main approaches in the literature to deal with these problems with a special emphasis to renewal theory to model the probabilistic structure of these optimization problems.

Suggested Citation

  • Rodríguez-Dagnino, Ramón M. & Takagi, Hideaki, 2010. "Application of renewal theory to call handover counting and dynamic location management in cellular mobile networks," European Journal of Operational Research, Elsevier, vol. 204(1), pages 1-13, July.
    • Handle: RePEc:eee:ejores:v:204:y:2010:i:1:p:1-13
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    References listed on IDEAS

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    1. Yamazaki, Genji & Toshimitsu, Satomu, 2001. "Light traffic in a cellular system with mobile subscribers and its applications," European Journal of Operational Research, Elsevier, vol. 135(1), pages 114-127, November.
    2. Machihara, Fumiaki & Saitoh, Midori, 2008. "Mobile customer model with retrials," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1073-1087, September.
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    Cited by:

    1. F. G. Badía & C. Sangüesa, 2017. "Log-Convexity of Counting Processes Evaluated at a Random end of Observation Time with Applications to Queueing Models," Methodology and Computing in Applied Probability, Springer, vol. 19(2), pages 647-664, June.

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