Age of Information Optimization in Aerial IRS-Assisted IoT communication system

In the intricate Internet of Things (IoT) communication system, the freshness of information is difficult to guarantee. Intelligent reflecting surface (IRS) can reconstruct the wireless propagation environment and improve communication performance. In this paper, we aim to minimize the mean age of information (AoI) for an IRS-assisted Unmanned Aerial Vehicle (UAV) IoT communication system by jointly optimizing the UAV trajectory, source schedule and IRS phase shift matrix. We decoupled the complex problem into two sub-problems and proposed a joint optimization algorithm to solve it. Firstly, we invoked the semi-definite relaxation (SDR) to adjust the phase shift matrix of IRS to get the maximum channel gain of the corresponding channel. Then we modeled the UAV trajectory and source schedule as a Markov Decision Process (MDP) and invoked the Dueling DQN algorithm to solve it. Simulation results verify the effectiveness of the proposed scheme for optimizing system AoI.