Pilot-Assisted AoI Minimization Scheme in the Finite Blocklength Regime

Abstract

This paper considers an industrial IoT (Internet of Things) status update system, where an industrial robot samples a physical process and sends short status packets to a BS. The timeliness of status updates is characterized by the recently proposed metric, age of information (AoI). We consider the BS cannot obtain the channel state information (CSI) in advance, and the robot needs to periodically send pilots to assist the BS to complete channel estimation. Considering that the robot needs to consume energy to send status packets and pilots, this paper aims to design a status update scheme to minimize the average AoI of the system while satisfying the energy consumption constraint. The optimization problem is formulated as a constrained Markov decision process (CMDP), and we prove the existence of optimal stationary scheme. However, due to the large dimension of the state space, traditional relative value iteration method has a high computational complexity. In this regard, we design a status update scheme with AoI threshold structure, and transform the status update scheme design problem into a convex optimization problem, and obtain a suboptimal status update scheme. Simulation results show that the proposed scheme outperforms the benchmark scheme, and achieves almost the same performance as the optimal scheme.