标题： 反馈在分布式数据收集中用于精确和节能的状态估计的优势 显示英文标题

标题： Advantages of Feedback in Distributed Data-Gathering for Accurate and Power-Efficient State-Estimation

摘要： 在分布式目标跟踪传感器网络中，高效的数据显示方法是必要的，以节省通信资源并保证信息准确性。 本文提出了一种反馈（FB）分布式数据显示方法，该方法让中心单元将信息反馈给移动传感器；然后每个传感器使用该信息来消除冗余传输并减少通信拥塞。 我们通过评估不同架构规范（例如，通信延迟率、功率成本率、最大退避时间、采样周期、观测噪声）下的可行性条件和优势条件，严格比较了其性能，包括均方误差（MSE）和每个传感器的功率成本。 在这里，我们将优势定义为FB相对于NF所获得的性能提升，而如果优势区域非空，则认为FB是可行的。 我们的理论分析表明，FB的可行性更多地取决于通信功率成本，而优势则取决于每个传输间隔的传感器传播延迟；我们推导出了这些结果成立的具体条件。 通过在各种设置下进行大量数值仿真，我们验证了推导条件的准确性，并展示了我们的理论结果即使在简化假设不再成立的更复杂场景中也仍然成立。 显示英文摘要

摘要： In distributed target-tracking sensor networks, efficient data gathering methods are necessary to save communication resources and assure information accuracy. This paper proposes a Feedback (FB) distributed data-gathering method which lets the central unit feed information back to the mobile sensors; each sensor then uses it to cancel redundant transmissions and reduce communication congestion. We rigorously compare its performance, in terms of mean-squared error (MSE) and cost of power per sensor, against more conventional Non-Feedback (NF) architectures by evaluating conditions of feasibility and advantage under different architecture specifications (e.g., communication delay rate, power cost rate, maximum back-off time, sampling period, observation noise). Here, we defined the advantage as the performance gain achieved by FB over NF, while FB is said to be feasible if the advantage region is nonempty. Our theoretical analyses show that the feasibility of FB depends more on the communication power cost, while the advantage depends on the sensors' propagation delay per transmission interval; we derive concrete conditions under which these outcomes hold. Using extensive numerical simulations under a variety of settings, we confirm the accuracy of the derived conditions, and show that our theoretical results hold even for more complex scenarios where the simplifying assumptions no longer hold.