AI 中文总结
研究基于能量收集和唤醒无线电的无人机物联网网络，通过将设备行为建模为离散时间马尔可夫链，利用随机几何和相关分析开发数学框架，揭示传输频率与能耗权衡，表明调整参数可提升能量效率和传输可靠性。
AI 中文摘要
本文研究了一种集成唤醒无线电（WuR）和能量收集以实现设备可持续运行的无人机物联网（IoT）架构。在所提出的系统中，无人机发送射频（RF）信号，既触发设备激活又补充存储能量。将物联网设备行为建模为离散时间马尔可夫链，考虑能量收集和消耗来捕捉其电池电量和运行状态（睡眠或唤醒）的演变。利用随机几何和离散时间马尔可夫链分析，开发了一个综合数学框架来评估系统性能。揭示了传输频率与能量消耗之间的权衡，并表明调整无人机密度等系统参数可显著提高能量效率和传输可靠性。
英文摘要
This paper investigates an unmanned aerial vehicle (UAV)-enabled Internet of Things (IoT) architecture that integrates wake-up radio (WuR) and energy harvesting for sustainable device operation. In the proposed system, UAVs transmit radio-frequency (RF) signals that both trigger device activation and replenish stored energy. The IoT device's behavior is modeled as a discrete-time Markov chain, which captures the evolution of its battery level and operational state (asleep or awake), accounting for both energy harvesting and energy consumption. Leveraging stochastic geometry and discrete-time Markov-chain analysis, we develop a comprehensive mathematical framework to assess system performance. We reveal a tradeoff between transmission frequency and energy consumption, and demonstrate that tuning of system parameters, such as UAV density, can significantly improve both energy efficiency and transmission reliability.
