A dual-branch cross-attention neural network with recurrent tracking reconstructs complete channel impulse responses from satellite imagery by predicting TDL parameters, reaching over 0.96 PDP cosine similarity on unseen sites.
Vision aided channel prediction for vehicular communications: A case study of received power prediction using RGB images
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
eess.IV 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Deep Learning-Based Site-Specific Channel Modeling and Inference
A dual-branch cross-attention neural network with recurrent tracking reconstructs complete channel impulse responses from satellite imagery by predicting TDL parameters, reaching over 0.96 PDP cosine similarity on unseen sites.