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

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...

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Bibliographic Details
Published in:ISWCS '04 : 1st International Symposium on Wireless Communication Systems 2004 : proceedings : 20-22 September, 2004, Mauritius pp. 85 - 89
Main Authors: Kuan, D.C.M., Yeo, B.S.
Format: Conference Proceeding
Language:English
Published: IEEE 2004
Subjects:
Bandwidth
Computer network management
Computer networks
Cost function
Intelligent networks
Land mobile radio cellular systems
Linear programming
Mathematical programming
Radio spectrum management
Shape
ISBN:0780384725, 9780780384729
Online Access:Get full text
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Summary: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.
ISBN:0780384725
9780780384729
DOI:10.1109/ISWCS.2004.1407214