Mse Minimized Scheduling For Multiple-Source Remote Estimation With Aoi Constraints In Iwsn

For typical monitoring and control applications in industrial wireless sensor network (IWSN), multiple sensor nodes periodically sample analog signals and send the digitalized data to the control center for remote estimation and further control. When the channel capacity is limited, the resource should be scheduled to minimize the time-average Mean Square Error (MSE) of the estimated signal. In this paper, we first formulate it as an MSE-minimized optimal scheduling problem with capacity constraint. Then we propose an optimized slot allocation strategy based on Lyapunov Optimization, which minimizes the drift-plus-penalty function considering the variance of the estimated signal and the Age of Information (AoI) from sensor nodes. Numerical results show that the proposed time slot allocation method can effectively reduce MSE compared to simple sequential allocation strategy.