A two-stage reinforcement learning system on pretrained LLMs aligns channel state information with user intents to generate adaptive, physically realizable link construction strategies for 6G that outperform conventional methods in experiments.
NR; Physical channels and modulation (Release 17),
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Agentic Link Construction for Environment and Intent Aware 6G Communication
A two-stage reinforcement learning system on pretrained LLMs aligns channel state information with user intents to generate adaptive, physically realizable link construction strategies for 6G that outperform conventional methods in experiments.