An Online Sensor Power Schedule for Remote State Estimation With Communication Energy Constraint

We consider sensor transmission power scheduling for remote state estimation with limited communication energy. A sensor needs to decide when to switch between different transmission energy levels in order to minimize the average expected estimation error covariance subject to the available energy budget. In the existing work the sensor only exploits the prior knowledge of the system parameters, the noise covariance and the channel characteristics but neglects the realtime information the estimator can provide. Thanks to the power asymmetry between the sensor and the estimator, we propose an online scheduling scheme which makes a choice based on the acknowledgement sequence at the remote estimator side and show that the scheme outperforms the optimal offline schedule under the same energy constraint.