Anchor-CKM reconstructs channel knowledge maps from sparse irregular measurements by constructing a pilot-supported representation with partial convolutions followed by layout-conditioned Fourier refinement, achieving 0.79-1.33 dB RMSE reduction versus baselines on DeepMIMO scenarios.
A tutorial on environment-aware communications via channel knowledge map for 6G
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CHARM extracts ADPS priors from path-level radio maps to reduce 3D angle-delay-AoD search to 1D AoD search per path, delivering 34.8x speedup over joint OMP at T≤4 pilots with comparable accuracy and only 3.7 dB degradation under 0.2 rad dictionary mismatch via trust-region constraint.
A unified parametric framework identifies active satellites and reconstructs RSS fields from measurements by linking beam geometry to spatial signal formation with adaptive complexity control.
citing papers explorer
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Channel Knowledge Map Reconstruction From Sparse Measurements via Pilot-Anchored Layout-Conditioned Fourier Refinement
Anchor-CKM reconstructs channel knowledge maps from sparse irregular measurements by constructing a pilot-supported representation with partial convolutions followed by layout-conditioned Fourier refinement, achieving 0.79-1.33 dB RMSE reduction versus baselines on DeepMIMO scenarios.
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Path-Level Radio Map-Aided Fast and Robust Channel Estimation for Pilot-Starved MIMO-OFDM Systems
CHARM extracts ADPS priors from path-level radio maps to reduce 3D angle-delay-AoD search to 1D AoD search per path, delivering 34.8x speedup over joint OMP at T≤4 pilots with comparable accuracy and only 3.7 dB degradation under 0.2 rad dictionary mismatch via trust-region constraint.
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Beam-Aware Radio Map Estimation With Physics-Consistent Parametric Modeling for Unknown Multiple Satellites
A unified parametric framework identifies active satellites and reconstructs RSS fields from measurements by linking beam geometry to spatial signal formation with adaptive complexity control.