An O-RAN-Assisted MARL Approach for Dynamic Sidelink and Infrastructure Selection in V2X Communications
This paper leverages Open RAN to manage V2X communication and proposes a multi-agent reinforcement learning (MARL) resource-aware system that aims to mitigate interference, optimize resource usage, and enhance quality of service by optimally selecting between sidelink and network transmissions.