Reinforcement learning agent optimizes DA-RoF transmitter parameters to achieve up to 2.7 dB SNR gains for high-order QAM modulations.
Enabling Optical Network Technologies for 5G and Beyond,
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AlignFed introduces a multi-stage semantic alignment mechanism for asynchronous federated fine-tuning of LLMs to mitigate model drift, client drift, and aggregation unfairness in heterogeneous edge environments.
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Reinforcement Learning-Enabled Agent for Transmitter Optimization in Digital-Analog Radio-over-Fiber Fronthaul
Reinforcement learning agent optimizes DA-RoF transmitter parameters to achieve up to 2.7 dB SNR gains for high-order QAM modulations.