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We study the performance of wireless links for a class of Poisson networks,in which packets arrive at the transmitters following Bernoulli processes. Bycombining stochastic geometry with queueing theory, two fundamental measuresare analyzed, namely the transmission success probability and the metadistribution of signal-to-interference-plus-noise ratio (SINR). Different fromthe conventional approaches that assume independent active states across thenodes and use homogeneous point processes to model the locations ofinterferers, our analysis accounts for the interdependency amongst activestates of the transmitters in space and arrives at a non-homogeneous pointprocess for the modeling of interferers' positions, which leads to a moreaccurate characterization of the SINR. The accuracy of the theoretical resultsis verified by simulations, and the developed framework is then used to devisedesign guidelines for the deployment strategies of wireless networks.

A Unified Framework for SINR Analysis in Poisson Networks with Traffic Dynamics