Fast Simulation of Cellular Networks with Dynamic Channel Assignment Felisa J. V´ azquez-Abad Department of Computer Science and Operations Research University of Montreal, Montreal, Canada H3C 3J7 Email: vazquez@iro.umontreal.ca also Principal Fellow, Department of Electrical and Electronic Engineering The University of Melbourne Lachlan L. H. Andrew and David Everitt ARC Special Research Centre for Ultra-Broadband Information Networks Department of Electrical and Electronic Engineering The University of Melbourne, Victoria 3010, Australia Email: l.andrew,d.everitt @ee.mu.oz.au Abstract Blocking probabilities in cellular mobile communication networks using dynamic channel assignment are hard to compute for realistic sized systems. This computational difficulty is due to the structure of the state space, which imposes strong coupling constraints amongst compo- nents of the occupancy vector. Approximate tractable models have been proposed, which have product form stationary state distributions. However, for real channel assignment schemes, the product form is a poor approximation and it is necessary to simulate the actual occupancy process in order to estimate the blocking probabilities. Meaningful estimates of the blocking probability typically require an enormous amount of CPU time for simulation, since blocking events are usually rare. Advanced simulation approaches use importance sampling (IS) to overcome this problem. In this paper we study two regimes under which blocking is a rare event: low load and high cell capacity. Our simulations use the standard clock (SC) method. For low load, we propose a change of measure that we call static ISSC, which has bounded relative error. For high capacity, we use a change of measure that depends on the current state of the network occupancy. This is the dynamic ISSC method. We prove that this method yields zero variance estimators for single clique models, and we empirically show the advantages of this method over na¨ ıve simulation for networks of moderate size and traffic loads. Supported in part by NSERC-Canada grant # WFA0184198. Supported by the Australian Research Council (ARC). 1