Joint optimization of scheduling and estimation policies is considered for a system with two sensors and two noncollocated estimators. Each sensor produces an independent and identically distributed sequence of random variables, and each estimator forms estimates of the corresponding sequence with respect to the mean-squared error sense. The data generated by the sensors are transmitted to the corresponding estimators over a bandwidth-constrained wireless network that can support a single packet per time slot. The access to the limited communication resources is determined by a scheduler that decides which sensor measurement to transmit based on both observations. The scheduler has an energy-harvesting battery of limited capacity, which couples the decision-making problem in time. Despite the overall lack of convexity of this problem, it is shown that this system admits a globally optimal scheduling and estimation strategy pair under the assumption that the distributions of the random variables at the sensors are symmetric and unimodal. Additionally, the optimal scheduling policy has a structure characterized by a threshold function that depends on the time index and energy level. A recursive algorithm for threshold computation is provided.

中文翻译：

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能量收集网络估计的最优调度策略

对于具有两个传感器和两个非并置估计器的系统，考虑对调度和估计策略进行联合优化。每个传感器产生独立且均匀分布的随机变量序列，并且每个估计器都针对均方误差意义形成相应序列的估计。传感器生成的数据通过带宽受限的无线网络传输到相应的估计器，该无线网络可以在每个时隙支持一个数据包。调度程序确定对有限通信资源的访问，该调度程序基于这两个观察来决定要发送的传感器测量值。调度程序具有容量有限的能量收集电池，这会及时耦合决策问题。尽管这个问题总体上没有凸性，结果表明，该系统在传感器的随机变量分布是对称且单峰的前提下，接受了全局最优调度和估计策略对。另外，最佳调度策略具有以阈值函数为特征的结构，该阈值函数取决于时间索引和能量水平。提供一种用于阈值计算的递归算法。