The proposed pretraining framework for safe DRL in CF-MIMO resource management doubles initial energy efficiency, achieves 4.7% higher final EE, maintains 1% delay violation rate, and cuts exploration steps by 50% compared to non-pretrained baselines while matching diffusion model performance at 14x
Time- sensitive networking-driven deterministic low-latency communication for real-time telemedicine and e-health services,
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Generative Learning Enhanced Intelligent Resource Management for Cell-Free Delay Deterministic Communications
The proposed pretraining framework for safe DRL in CF-MIMO resource management doubles initial energy efficiency, achieves 4.7% higher final EE, maintains 1% delay violation rate, and cuts exploration steps by 50% compared to non-pretrained baselines while matching diffusion model performance at 14x