论文标题

在多类空间出生和死亡过程中,无线型相互作用

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

论文作者

Popineau, Pierre, Baccelli, François

论文摘要

本文研究了欧几里得平面建模无线相互作用的多类空间出生和死亡(SBD)过程。在此模型中,用户达到了恒定的速率,并以网络中其他用户创建的干扰的比率函数离开。这项工作的新颖性在于增加服务差异化,这是受5G网络中存在的带宽分区的启发:用户分配了固定数量的频段,并且仅干扰这些频段上的传输。本文的第一个结果是确定系统在随机上稳定的关键用户到达率,而在该系统是不稳定的。分析需要论文中定义的对称假设。结果的证明使用随机单调性和流体极限模型。单调性使一个人可以通过两个适当的离散状态马尔可夫跳跃过程将动力学从上和下面绑定,我们使用流体限制获得了稳定性和不稳定性结果。这导致了关键到达率的封闭形式表达式。第二个贡献包括两个启发式方法,以估计网络中所有类别用户的稳态密度:第一个依赖于稳态过程的泊松近似。第二个使用二阶测量的空腔近似,这导致对稳态用户密度的更准确估计。 Poisson启发式方法还为关键到达率提供了良好的估计。

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.

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