Generating snapshots and analyzing missed traffic in wireless communications

We propose a static model of a single service UMTS network which, unlike existing static models, includes variability of network performance but is less complex than a dynamic model. We study two methods to reduce the running time of the Monte Carlo simulation program. We link a complex multiple- cell model back to a simpler single-cell model and classify snapshots of the simulation program into classes based on their network performance. The classification rule will be used to increase the probability of directly creating snapshots with some prescribed network performance, and is based on the average squared distance between terminals and serving base station. At a realistic setting of the parameters this results in a maximum reduction of the running time by a factor 5