The multi-action transmission scheduling problem for remote state estimation under global energy constraint
<p>Xu Fanghui</p> · Academic Journal of Computing & Information Science · 2023
This paper proposes a multi-action transmission scheduling problem for remote state estimation in wireless networked physical systems under global energy constraints. Firstly, the system state estimation is obtained through Kalman filtering. Then, the estimated values are transmitted from sensors to a remote estimator through randomly fading channel. Unlike traditional transmission scheduling problems, the proposed system model allows sensors to choose from multiple power levels at each decision node. Additionally, the study considers global energy constraint and formulates the system model as a constrained Markov decision process to obtain the optimal transmission strategy that minimizes the average estimation error covariance at the remote estimator over an infinite time horizon. Through model transformation, a important conclusion is derived. As the average estimation error covariance at the remote estimator increases, the optimal transmission power exhibits an increasing trend. This conclusion extends the threshold structure of the optimal strategy to a monotonic increasing structure. Finally, the theoretical result is verified through numerical simulations.