ChannelLM-driven digital twin architecture reduces channel prediction error by 4.23 dB in unseen environments versus small AI models while achieving 70 ms end-to-end latency.
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Paradigm Shift from Statistical Channel Modeling to Digital Twin Prediction: An Environment-Generalizable ChannelLM for 6G AI-enabled Air Interface
ChannelLM-driven digital twin architecture reduces channel prediction error by 4.23 dB in unseen environments versus small AI models while achieving 70 ms end-to-end latency.