Reinforcement Learning Boosts Network Slicing in 5G-Advanced O-RAN
A reinforcement learning framework improved bandwidth slicing in 5G-advanced O-RAN simulations, while tabular Q-learning struggled with large-state beam selection.
A reinforcement learning framework improved bandwidth slicing in 5G-advanced O-RAN simulations, while tabular Q-learning struggled with large-state beam selection.
An attention-enhanced meta-reinforcement learning scheduler reduced URLLC violations to 63.11% versus 90.54% for DQN and 79.52% for PPO in single-cell ...
Researchers have proposed a multiuser framework that combines fluid antenna systems with NOMA to significantly improve the reliability of short-packet ...
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© 2025 Scienmag - Science Magazine