Robust transmission power management for remote state estimation with wireless energy harvesting

Wireless energy harvesting is an emerging technology in the Internet of things (IoT). Plenty of recent literature focused on balancing the information transfer and energy harvesting at the same time. Different from these works, we jointly consider the remote state estimation and wireless energy harvesting in IoT, and introduce a new cost function which is the weighted difference between the remote state estimation error at the estimator side and the harvested energy at the energy receiver side. In our framework, the collection of communication channel states is known as a priori knowledge and the real-time channel state is not known. We consider the scenario that the transmitter can send the observation data for remote estimation and deliver the power for energy harvesting concurrently. A robust transmission power split algorithm is provided to minimize the cost function for the worst-case channel state. In addition, another robust power switch algorithm is designed for the scenario that the transmitter can only decide to send the observation data or deliver the power for energy harvesting at any time slot. At last, simulation examples are provided to show the effectiveness of our proposed robust transmission power allocation policies.