2 papers with code • 0 benchmarks • 0 datasets
Intelligently decide how to simultaneously conduct radar and communication over a shared radio channel.
These leaderboards are used to track progress in Joint Radar-Communication
Deep Reinforcement Learning for Time Allocation and Directional Transmission in Joint Radar-Communication
In addition, experimental results show that the trained deep reinforcement learning agents are robust to changes in the number of vehicles in the environment.
In this paper, we propose a framework for intelligent vehicles to conduct JRC, with minimal prior knowledge of the system model and a tunable performance balance, in an environment where surrounding vehicles execute radar detection periodically, which is typical in contemporary protocols.