Abstract

This paper investigates the problem of sensor power control for the scenario of remote state estimation. Most existing works mainly focus on designing sensor power scheduling schemes to minimize average estimation errors or terminal estimation errors when the sensor’s transmission capability is restrained by the energy budget. By contrast with these objectives, we aim to balance the cost of sensor power and the quality of remote estimation in this work. Specifically, we are interested in the problem that minimizes the expected weighted average sum of the remote state estimation errors and the sensor’s transmission power costs in an infinite time horizon. A Markov decision process framework is adopted to present the structure of the optimal power control strategy. However, it is not possible to find an analytical expression of the optimal solution. Thus, we further present an approximation solution and then derive a suboptimal sensor power control strategy. Finally, a simulation example is provided to show the effectiveness of our designed sensor control strategy.

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