PILOT unifies 2D and 3D radio map generation via physics-guided wavefront autoregressive prediction, reporting lowest NMSE on 2D benchmarks and 78% NMSE reduction with 2500x faster inference than diffusion baselines for 3D.
Llm4pg: Adapting large language model for pathloss map generation via synesthesia of machines
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A unified framework for CSI-native foundation models incorporates scale-aware exposure, physical coordinates, and correlation-bounded attention, reporting over 4 dB NMSE gains in zero-shot tasks and 36.6% spectral efficiency improvement with 7% pilot overhead.
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PILOT: One Physics-Integrated Generation Framework to Unify 2D and 3D Radio Map Construction
PILOT unifies 2D and 3D radio map generation via physics-guided wavefront autoregressive prediction, reporting lowest NMSE on 2D benchmarks and 78% NMSE reduction with 2500x faster inference than diffusion baselines for 3D.
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Towards CSI-Native Foundation Models: A Channel-Adaptive Roadmap for 6G
A unified framework for CSI-native foundation models incorporates scale-aware exposure, physical coordinates, and correlation-bounded attention, reporting over 4 dB NMSE gains in zero-shot tasks and 36.6% spectral efficiency improvement with 7% pilot overhead.