GeoUQ-GFNet reconstructs dense urban gain radio maps from sparse measurements using geometry priors and uncertainty-guided active sensing, showing consistent gains over non-adaptive sampling on the new UrbanRT-RM ray-tracing benchmark.
CKMImageNet: A dataset for AI-based channel knowledge map towards environment- aware communication and sensing
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A single channel knowledge map built for communication can be directly reused for NLoS sensing by transforming angle-delay priors via virtual UE modeling, yielding better localization than geometry-based methods in simulations.
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Sparse Gain Radio Map Reconstruction With Geometry Priors and Uncertainty-Guided Measurement Selection
GeoUQ-GFNet reconstructs dense urban gain radio maps from sparse measurements using geometry priors and uncertainty-guided active sensing, showing consistent gains over non-adaptive sampling on the new UrbanRT-RM ray-tracing benchmark.
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You May Use the Same Channel Knowledge Map for Environment-Aware NLoS Sensing and Communication
A single channel knowledge map built for communication can be directly reused for NLoS sensing by transforming angle-delay priors via virtual UE modeling, yielding better localization than geometry-based methods in simulations.