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A non-linear binary integer programming model for location area partitioning in cellular radio networks

Authors: Daniel Chien Ming Kuan; Boon Sain Yeo;

A non-linear binary integer programming model for location area partitioning in cellular radio networks

Abstract

The scarce radio resources available to any cellular radio network have to be shared between its revenue-generating voice- and data-carrying services, and non-revenue-generating management services. One of these management services is location management, crucial for the network to keep track of the location of its subscribers and to connect their incoming calls. Location management consists of the two activities, paging and location updating, both of which are structured around a subdivision of the network service area called the location area (LA). The ways in which the service area is partitioned therefore has a direct impact on the amount of radio bandwidth that has to be spent on location management. However, paging and location updating share an antagonistic relationship, and finding the optimal LA partitioning that strikes a balance between the two is a challenging design problem. In this paper, the problem of finding the optimal LA partitioning of a cellular radio network service area in order to minimise the total location management signalling cost is addressed. The choice of the decision variables used in the mathematical programming model results in an objective function that is conceptually easy to understand and a solution method that is simple and straightforward.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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