DQN based Anti-blocking Routing Algorithm for IRS-assisted MANET

Mobile ad-hoc networks (MANETs) have garnered significant interest in various specific scenarios owing to their capability to provide flexible and decentralized communication. However, in MANETs, link failures caused by obstacles, traffic surges and inefficient routing algorithms, are commonly en-countered. To address these issues, we propose an intelligent reflecting surface assisted anti-blocking routing (IRS-ABR) algorithm that incorporates the deep Q-network (DQN) for dynamic obstacles avoidance and traffic control. Moreover, by employing IRSs as intermediate nodes in the network, the proposed algorithm can achieve enhanced path routing. The simulation results validate the effectiveness of the proposed algorithm, as it achieves a 50% higher packet delivery rate compared to the traditional algorithm, while also reducing the transmission delay and energy consumption by 34% and 12%, respectively, through the utilization of IRS.