Multisensor Transmission Scheduling for State Estimation Over Multihop Networks in a Cyber–Physical System Environment
研究了多跳网络中多传感器传输调度问题，提出最优调度策略以最小化远程终端单元的估计误差协方差和传输成本，并在IEEE 118节点系统上验证了有效性。
This article investigates the multisensor transmission scheduling problem for state estimation over multihop networks. Unlike single-sensor scheduling for multihop networks, the communication coupling of multisensor makes the design of transmission scheduling more complex. In view of this, we focus on finding the optimal multisensor transmission scheduling to minimize the estimation error covariance of the remote terminal units (RTUs) and transmission costs. First, the transmission scheduling problem is formulated as the Markov decision process (MDP) in the scenarios of smart relays and traditional relays, respectively. Second, we propose the optimal multisensor transmission scheduling strategy, which is rigorously proved to be monotonic with respect to the number of consecutive packet losses for two relay types. Third, the necessary and sufficient conditions (NSCs) are given to guarantee system stability under the constructed transmission scheduling. Finally, the effectiveness of the proposed multisensor transmission scheduling is verified by the IEEE 118-bus system.