A Lyapunov-guided diffusion-based reinforcement learning algorithm is proposed for joint channel, power, and altitude decisions in UAV-assisted vehicular networks with delayed CSI, outperforming three baselines in simulation.
Leveraging UA Vs for coverage in cell-free vehicular networks: A deep reinforcement learning approach,
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A Lyapunov-Guided Diffusion-Based Reinforcement Learning Approach for UAV-Assisted Vehicular Networks with Delayed CSI Feedback
A Lyapunov-guided diffusion-based reinforcement learning algorithm is proposed for joint channel, power, and altitude decisions in UAV-assisted vehicular networks with delayed CSI, outperforming three baselines in simulation.