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 larger for the increasing convex stochastic order. As a corollary, mean workload and mean delay improve as network mobility increases. Positive correlation between SINR level-crossing events at different time points is established and the autocorrelation function is determined. System behaviour is empirically analyzed using discrete-event simulation. The performance of various mobility models is evaluated using heavy-traffic approximations.
翻译:本文审视了在Poisson点移动无线干扰器过程中嵌入的队列的时间演进过程。 队列是由外部抵达过程驱动的, 并受到时间变化式服务过程的影响, 这是它所看到的SINR的函数 。 干扰器的静态配置导致无限的队列工作量, 且呈积极概率 。 相反, 当干扰器拥有任何非零移动性, 从而导致在不同时间点上独立的干扰器和不易干扰器位置的流离失所时, 为队列设定了一个通用的稳定条件 。 证据利用 Poisson 点进程的混合属性。 也会研究增加排队列指标的流动性的效果。 Convex 排序工具用来确定快速移动干扰器导致的队列工作量, 而对于增加的 convex 随机顺序来说,这种工作量更大。 作为必然结果, 平均工作量和延迟会随着网络流动性的增加而改善。 将确定SINR在不同时间点上跨层事件与自动连接功能之间的正相关关系。 系统行为是使用离心- 模拟进行实验性分析的系统行为 。 使用重度 模拟对各种移动模型的性进行了评估。