Stochastic Geometry Modeling and Analysis of Statistical Priority-based Multiple Access Protocol

Statistical priority-based multiple access protocol (SPMA) has attracted more and more attention in virtue of its support for multi-priority traffic, and the guarantee of low-latency and high-reliability transmissions for the high-priority traffic. In this work, we propose an analytical framework to study the performance of SPMA from a spatial perspective using stochastic geometry. We consider two kinds of priority users, and mainly focus on the medium access probability (MAP) of low-priority users, taking into account the potential transmitter (PT) density, ratio of different traffic users, amount of orthogonal resources, channel occupancy statistics (COS) threshold, and statistical sliding window (SSW). We first propose a new statistical model to calculate the probability mass function (PMF) of COS in a unit time interval, and then provide two approaches to derive the PMF of COS over any given SSW. The proposed analytical framework allows to quantify the effect of key parameters on the MAP, and provides guidelines on the design of COS threshold in terms of the MAP.