Demand modeling and growth planning for TDMA-based wireless networks

Abstract
Wireless service providers are facing the need to plan and rapidly evolve their networks to meet subscriber demands. This includes adding switching and radio equipment. At the same time, providers want to maximize the return on their investment by yielding the most subscriber capacity from their network. As networks evolve, large numbers of base transceiver stations (BTSs) along with base station controllers (BSCs) and mobile switching centers (MSCs) are added to support subscriber growth and demand. How to deploy this equipment and maximize performance is a complex problem, which calls for sound and useful methodologies. In order to assess the performance of the network, the subscriber's impacts must be known. Without the understanding of how the subscribers will tax the network resources, the providers will not be able to make the most of their investment and ensure quality and grade of service. This paper proposes techniques for modeling subscriber demand and behavior, which is the key in determining how networks will perform as the subscriber base grows and the network evolves. These scientific techniques were developed to generate accurate representations of subscriber behavior to be used in the planning of wireless networks.

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