RA-QAGC combines rate-aware graph condensation with quantum annealing and RL to optimize multi-UAV trajectories, reporting 15-34% throughput gains in simulations.
Dqn-based joint uav trajectory and association planning in ntn-assisted networks,
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Rate-Aware Quantum-Inspired Trajectory Learning for Interference-Limited Multi-UAV Networks
RA-QAGC combines rate-aware graph condensation with quantum annealing and RL to optimize multi-UAV trajectories, reporting 15-34% throughput gains in simulations.