Multi-sensor Transmission Power Scheduling for Remote State Estimation under SINR Model

In this paper, we consider multi-sensor transmission power scheduling for remote state estimation. Each sensor measures its corresponding process and then sends the local estimate to a remote estimator through a shared wireless channel. Due to the interference from other sensors and the channel noise, packet drop occurs. Each sensor needs to decide the transmission power individually to maximize the estimation performance subject to an energy constraint in this multi-player game under signal-to-interference-plus-noise ratio (SINR) model. As the Nash equilibrium of the game may not be Pareto optimal, we propose mixed strategies for each sensor using the online information which can improve the estimation performance for all sensors. Comparison and simulation of three typical power schedules are then provided.