论文标题
动态资源优化，用于分散估计的能源收集物联网网络的估计
Dynamic Resource Optimization for Decentralized Estimation in Energy Harvesting IoT Networks
论文作者
论文摘要
我们研究融合中心的时变信号的分散估计，当能量收集传感器通过速率受限的链接传输采样数据时。我们提出了动态策略，以在每个节点处选择无线电参数，采样集和收获的能量，以估计一个随时间变化的信号，同时确保：i）恢复过程的准确性，ii）电池在规定的工作水平围绕规定的工作水平的稳定性。该方法基于随机优化工具，该工具可以在不需要了解无线电通道和能量到达过程的统计数据的情况下进行自适应优化。数值结果验证了在通信和物联网（IoT）场景的典型的通信和能量约束下进行分散信号估计的拟议方法。
We study decentralized estimation of time-varying signals at a fusion center, when energy harvesting sensors transmit sampled data over rate-constrained links. We propose dynamic strategies to select radio parameters, sampling set, and harvested energy at each node, with the aim of estimating a time-varying signal while ensuring: i) accuracy of the recovery procedure, and ii) stability of the batteries around a prescribed operating level. The approach is based on stochastic optimization tools, which enable adaptive optimization without the need of apriori knowledge of the statistics of radio channels and energy arrivals processes. Numerical results validate the proposed approach for decentralized signal estimation under communication and energy constraints typical of Internet of Things (IoT) scenarios.
