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DMTT is the only decentralized federated learning method that maintains high accuracy against adversarial attacks while ensuring Byzantine influence is effectively minimized.
Reinforcement learning can drastically cut retraining costs in O-RAN without sacrificing performance, challenging traditional methods that rely on costly retraining.
Predicting user scheduling states can recover up to 73% of the sum rate loss caused by backhaul delays in coordinated beamforming systems.
