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Performance analysis of ambient RF energy harvesting: A stochastic geometry approach

机译：环境射频能量收集的性能分析：一种随机几何方法

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摘要

Ambient RF (Radio Frequency) energy harvesting techniques have recently been proposed as a potential solution to provide proactive energy replenishment for wireless devices. This paper aims to analyze the performance of a battery-free wireless sensor powered by ambient RF energy harvesting using a stochastic-geometry approach. Specifically, we consider a random network model in which ambient RF sources are distributed as a Ginibre α-determinantal point process which recovers the Poisson point process when α approaches zero. We characterize the expected RF energy harvesting rate. We also perform a worst-case study which derives the upper bounds of both power outage and transmission outage probabilities. Numerical results show that our upper bounds are accurate and that better performance is achieved when the distribution of ambient sources exhibits stronger repulsion.
机译：最近已经提出了环境RF（射频）能量收集技术，作为为无线设备提供主动能量补充的潜在解决方案。本文旨在分析采用随机几何方法通过环境射频能量收集供电的无电池无线传感器的性能。具体来说，我们考虑一个随机网络模型，其中将周围的RF源作为吉尼伯勒α-确定点过程进行分配，当α接近零时，该过程恢复了泊松点过程。我们表征了预期的射频能量收集率。我们还进行了最坏情况研究，得出了停电和传输中断概率的上限。数值结果表明，我们的上限是准确的，并且当环境源的分布表现出较强的排斥力时，可以实现更好的性能。

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