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

We study the performance of wireless links for a class of Poisson networks,\nin which packets arrive at the transmitters following Bernoulli processes. By\ncombining stochastic geometry with queueing theory, two fundamental measures\nare analyzed, namely the transmission success probability and the meta\ndistribution of signal-to-interference-plus-noise ratio (SINR). Different from\nthe conventional approaches that assume independent active states across the\nnodes and use homogeneous point processes to model the locations of\ninterferers, our analysis accounts for the interdependency amongst active\nstates of the transmitters in space and arrives at a non-homogeneous point\nprocess for the modeling of interferers' positions, which leads to a more\naccurate characterization of the SINR. The accuracy of the theoretical results\nis verified by simulations, and the developed framework is then used to devise\ndesign guidelines for the deployment strategies of wireless networks.\n