Modeling techniques for large-scale PCS networks

Abstract

Over the past few years there has been rapid growth in the demand for mobile communications that has led to intensive research and development of complex PCS (personal communication services) networks. Capacity planning and performance modeling are necessary to maintain a high quality of service to the PCS subscriber while minimizing costs. Effective and practical performance models for large-scale PCS networks are currently available. Two new performance models are presented in this article which can be solved using analytical techniques. The first is the so-called portable population model, based on the flow equivalent assumption (the rate of portables into a cell equals the rate of portables out of the cell). The model provides the steady-state portable population distribution in a cell that is independent of the portable residual time distribution, which can be used by simulations to reduce the necessary execution time by reaching the steady state more rapidly. Additionally, this model can be used to study the blocking probability of a low (portable) mobility PCS network and the performance of portable deregistration strategies. The second model is the so-called portable movement model which can be used to study location tracking and handoff algorithms. The model assumes that the arriving calls to a portable form a Poisson process, and portable residual times have a general distribution. This model can be used to study location-tracking algorithms and handoff algorithms. it is shown that under some assumptions, the analytic techniques are consistent with the simulation model.