On multiclass spatial birth-and-death processes with wireless-type interactions

TL;DR

This paper analyzes a multiclass spatial birth-and-death process modeling wireless networks with bandwidth partitioning, deriving stability conditions and proposing heuristics for steady-state user densities.

Contribution

It introduces a stability analysis for multiclass wireless SBD processes with bandwidth partitioning and proposes new heuristics for estimating steady-state densities.

Findings

Derived a closed-form critical arrival rate for stability.

Proposed Poisson and cavity heuristics for steady-state densities.

Validated heuristics with accurate estimates of critical rates.

Abstract

This paper studies a multiclass spatial birth-and-death (SBD) processes on a compact region of the Euclidean plane modeling wireless interactions. In this model, users arrive at a constant rate and leave at a rate function of the interference created by other users in the network. The novelty of this work lies in the addition of service differentiation, inspired by bandwidth partitioning present in 5G networks: users are allocated a fixed number of frequency bands and only interfere with transmissions on these bands. The first result of the paper is the determination of the critical user arrival rate below which the system is stochastically stable, and above which it is unstable. The analysis requires symmetry assumptions which are defined in the paper. The proof for this result uses stochastic monotonicity and fluid limit models. The monotonicity allows one to bound the dynamics from above and below by two adequate discrete-state Markov jump processes, for which we obtain stability and instability results using fluid limits. This leads to a closed form expression for the critical arrival rate. The second contribution consists in two heuristics to estimate the steady-state densities of all classes of users in the network: the first one relies on a Poisson approximation of the steady-state processes. The second one uses a cavity approximation leveraging second-order moment measures, which leads to more accurate estimates of the steady-state user densities. The Poisson heuristic also gives a good estimate for the critical arrival rate.