Transmission Schedule for Remote State Estimation in CPSs With Energy Harvesting and Sharing Two-Hop Networks

This paper investigates the problem of optimizing the transmission schedule between a sensor and a relay in cyber-physical systems to achieve accurate remote state estimation. The considered system model represents the plant as a linear time-invariant system, wherein the sensor measurements are transmitted to the remote estimator using an intelligent relay. Both the sensor and relay nodes are capable of harvesting energy from the external environment, and they are required to make transmission decisions at each time step to ensure the stability of system’s operation. In addition, energy sharing between each other can yield significant advantages by capitalizing on the available battery power and maximizing energy harvesting from the external environment. We describe the problem of finding the optimal transmission schedule as a dynamic programming model, and establish structural properties on the optimal schedule of the sensor and relay nodes, more precisely, (i) for given battery levels and harvested energy, the optimal transmission strategy is to transmit the measurements when the error covariances at the relay and the remote estimator meet certain conditions, (ii) for given harvested energy and error covariances at the relay and the remote estimator, the optimal transmission strategy is a threshold-based strategy on the battery levels.