可重构智能表面辅助无线电能传输系统的电池充电时间模型
Battery Recharging Time Models for Reconfigurable Intelligent Surface-Assisted Wireless Power Transfer Systems
摘要：
在本文中，我们开发了一个分析框架的可重构智能表面（RISs）辅助无线电力传输（WPT）系统的电池充电时间（BRT）的统计分析。具体而言，我们推导出新的封闭形式的概率密度函数（PDF），累积分布函数，和时刻的BRT的射频能量收集无线节点的表达式。此外，封闭形式的表达式的快速公交系统的PDF获得两种特殊情况下：i）当RIS配备有一个反射元件（RE），ii）当RIS由大量的REs.Capitalizing派生的表达式，我们提供了一个全面的处理BRT的统计特性，并研究系统和电池参数对其性能的影响。我们的研究结果表明，所提出的统计模型在分析上是易于处理的，准确的，有效的评估的可持续性的RIS辅助WPT网络，并在大规模的未来无线应用提供关键的设计见解。例如，我们证明，减少4倍的BRT的平均时间可以通过增加一倍的RIS元素的数量来实现。蒙特卡罗模拟结果证实了所提出的理论框架的准确性。
英文摘要：
In this paper, we develop an analytical framework for the statistical analysis of the battery recharging time (BRT) in reconfigurable intelligent surfaces (RISs) aided wireless power transfer (WPT) systems. Specifically, we derive novel closed-form expressions for the probability density function (PDF), cumulative distribution function, and moments of the BRT of the radio frequency energy harvesting wireless nodes. Moreover, closed-form expressions of the the PDF of the BRT is obtained for two special cases: i) when the RIS is equipped with one reflecting element (RE), ii) when the RIS consists of a large number of REs. Capitalizing on the derived expressions, we offer a comprehensive treatment for the statistical characterization of the BRT and study the impact of the system and battery parameters on its performance. Our results reveal that the proposed statistical models are analytically tractable, accurate, and efficient in assessing the sustainability of RIS-assisted WPT networks and in providing key design insights for large-scale future wireless applications. For example, we demonstrate that a 4-fold reduction in the mean time of the BRT can be achieved by doubling the number of RIS elements. Monte Carlo simulation results corroborate the accuracy of the proposed theoretical framework.
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