Reinforcement Learning Based Routing For Deadline-Driven Wireless Communication.

The objective of our work is to address the challenge of delivering time-sensitive data across a multi-hop wireless network. We aim to maximize the number of packets that reach their destination before the strict deadline. To achieve this, we introduce a deep reinforcement learning (DRL) approach that determines the optimal route, scheduling, and power allocation for each flow while complying with strict time constraints.