State-dependent stochastic mobility model in mobile communication networks

We apply finite state-dependent queueing networks to model mobility in mobile communication systems. Although they have been successfully used in the past to model vehicular traffic, state-dependent models have not been applied to mobile communication systems, to the best of our knowledge. The novelty of state-dependent stochastic mobility models is that the congestion phenomenon is explicitly considered, that is, the user speeds fall when the number of users in the system increases. We present a detailed description of the simulation model used to estimate the performance measures of the queueing networks and show computational results for a comprehensive set of instances. As we show, finite state-dependent stochastic models bring interesting new insights, for instance, that in some cases mixed bimodal distributions will better describe the cell residence time of a call than the classical probability distributions used in the past.