A hierarchical DRL method (TBH-DDPG) optimizes UAV trajectories at coarse granularity and bandwidth allocation at fine granularity, reporting 44.44% faster convergence and 58.05% lower computational cost than a non-hierarchical baseline in simulations.
Trajectory design for UA V-based Internet of Things data collection: A deep reinforcement learning approach
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UAV Trajectory and Bandwidth Allocation for Efficient Data Collection in Low-Altitude Intelligent IoT: A Hierarchical DRL Approach
A hierarchical DRL method (TBH-DDPG) optimizes UAV trajectories at coarse granularity and bandwidth allocation at fine granularity, reporting 44.44% faster convergence and 58.05% lower computational cost than a non-hierarchical baseline in simulations.