Interference Queueing Networks: A Replica Mean-Field Approach in the Symmetric Setting
arXiv:2606.13264
The paper models a wireless communication network as interacting queues whose service rates depend on the SINR, derives its stability region, and analyzes the stationary regime using two mean‑field approximations, proving exponential convergence to stationarity.
Abstract
We propose a model for evaluating the performance of wireless communication networks beyond the ubiquitous full-buffer assumption, under which every transmitter is always active. The network is represented by N interacting queues arranged on a torus, with homogeneous arrival rate and service rates depending on the activity of neighboring interferers. More precisely, each queue is associated with a transmitter-receiver pair, and its service rate is given by the Shannon capacity, which depends on the corresponding Signal-to-Interference-plus-Noise Ratio (SINR). Since interfering transmitters only emit when their queue is non-empty, the SINR, and hence the service rate, improves when neighboring queues are empty. We first derive the stability region of the system. To investigate the stationary regime, we introduce two mean-field approximations. The first one is obtained from a finite K-replica system, for which we prove propagation of chaos as K goes to infinity. The second one describes a queueing system evolving in a suitably chosen autonomous environment. We derive quantitative estimates comparing these two approximations. Finally, we prove that the original interacting queueing system converges exponentially fast to stationarity.