AoI Minimization Scheme for Short-Packet Communications in Energy-Constrained IIoT

Abstract

This paper is motivated by the requirement of high information freshness in the industrial Internet of Things (IIoT). An industrial robot sends short status packets to a control center (CC), and the timeliness of status updates is measured by the age of information (AoI). Due to the dynamic change of the wireless channel, the robot needs to send a pilot for channel estimation during each coherence time. Considering the robot is energy-limited, we investigate the average AoI minimization scheme for short packet communications under the average power consumption constraint. By rationally analyzing state transitions, we first formulate the problem as a constrained Markov Decision Process, and obtain the optimal solution through linear programming (LP). Then, for the problem of high computational complexity caused by too many variables in LP, we propose a heuristic threshold-based status update scheme by exploiting the threshold structure of the optimal solution. Simulation results show that the LP scheme can effectively minimize the average AoI and the threshold-based scheme can achieve near-optimal performance. Interestingly, we find that when the channel suffers from severe fading, at the end of a coherence time, the robot does not send status packets even if the information at the CC is particularly stale.