Ergodicity and steady state analysis for interference queueing networks

Abstract

We analyze an interacting queueing network on Z d \mathbb {Z}^d that was introduced in Sankararaman, Baccelli and Foss (2019) as a model for wireless networks. We show that the marginals of the minimal stationary distribution have exponential tails. This is used to furnish asymptotics for the maximum steady state queue length in growing boxes around the origin. We also establish a decay of correlations which shows that the minimal stationary distribution is strongly mixing, and hence, ergodic with respect to translations on Z d \mathbb {Z}^d .