Evaluation of Blocking Probability for Downlink in Poisson Networks

Abstract

In recent years, wireless network modeling using stochastic geometry tools, like Poisson Point Process (PPP), has acquired the attention of researchers. Modeling of interference, coverage, and capacity for cellular networks using PPP is presented in literature. However, the blocking probability remains to be investigated. In this letter, we present an analytical framework for evaluation of network blocking probability for downlink. The services can be categorized using multiple classes based on the average resource units required by the service. The multi-class service scenario is modeled using multi-dimensional Markov Chain. The Markov chain is further approximated using the Erlang approximation method to evaluate the activity factor of a base station (BS). Moreover, an approximate closed form expression for coverage probability is derived, which is applicable to interference as well as noise limited scenario. Exploiting the coupling between coverage and activity factor, we determine the class-wise arrival rate. Further, the class-wise arrival rates are used to determine the networks blocking probability. We validate the proposed analytical framework through the extensive simulation.