A GAT-LSTM-DQN routing framework for LEO satellites outperforms baselines on throughput, delay, and queue length in simulations by treating routing as a POMDP.
GRLR: Routing with graph neural network and reinforcement learning for mega LEO satellite constellations
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Spatial-Temporal Learning-Based Distributed Routing for Dynamic LEO Satellite Networks
A GAT-LSTM-DQN routing framework for LEO satellites outperforms baselines on throughput, delay, and queue length in simulations by treating routing as a POMDP.