Performance analysis of user association policies in small cell networks using Stochastic Petri Nets

This paper studies queuing performance of user association policies in small cell networks (SCNs). Most studies in this field have used static interference models for interfering base stations. However, the number of users associated with a Low Power Node (LPN) in a SCN is small and thus the interference situations may dynamically change. In this paper, we study a dynamic interference model, which considers both the fast fading effects of the wireless channel and the dynamic interference effects. We employ the Discrete Time Markov Chain (DTMC) to solve the model. Since the state space of DTMC increases exponentially with the user number, we use the model decomposition and iteration method in Stochastic Petri Nets to obtain the approximate value. Finally, we verify our analytical results through simulations.