Practical Cross-Band Channel Prediction for AI-RAN
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Practical Cross-Band Channel Prediction for AI-RAN via Physics-Guided Deep Unfolding
arXiv:2605.31279v1 Announce Type: cross Abstract: To make cross-band channel prediction practical for AI-native RAN, algorithms must generalize across diverse environments and support real-time inference. Existing approaches achieve one but not both. To bridge this gap, we introduce GUIDE, a physics-guided deep unfolding framework that embeds wireless channel physics into differentiable layers.