How wireless queues benefit from motion: an analysis of the continuum between zero and infinite mobility

TL;DR

This paper analyzes how mobility of wireless interferers influences queue stability and workload, showing that increased mobility generally reduces queue size and delay through stochastic ordering and autocorrelation analysis.

Contribution

It establishes a stability condition for queues with mobile interferers and demonstrates that higher mobility decreases workload and delay using stochastic ordering and autocorrelation analysis.

Findings

Mobility ensures queue stability where static interferers cause infinite workload.

Faster moving interferers lead to smaller queue workloads and delays.

Autocorrelation of interference decreases with increased mobility.

Abstract

This paper considers the time evolution of a queue that is embedded in a Poisson point process of moving wireless interferers. The queue is driven by an external arrival process and is subject to a time-varying service process that is a function of the SINR that it sees. Static configurations of interferers result in an infinite queue workload with positive probability. In contrast, a generic stability condition is established for the queue in the case where interferers possess any non-zero mobility that results in displacements that are both independent across interferers and oblivious to interferer positions. The proof leverages the mixing property of the Poisson point process. The effect of an increase in mobility on queueing metrics is also studied. Convex ordering tools are used to establish that faster moving interferers result in a queue workload that is smaller for the increasing-convex stochastic order. As a corollary, mean workload and mean delay decrease as network mobility increases. This stochastic ordering as a function of mobility is explained by establishing positive correlations between SINR level-crossing events at different time points, and by determining the autocorrelation function for interference and observing that it decreases with increasing mobility. System behaviour is empirically analyzed using discrete-event simulation and the performance of various mobility models is evaluated using heavy-traffic approximations.