A new open-source simulator and a characterized 200TB, 25M-frame synthetic radio dataset with 100 modulation classes, intended to train AI models for spectrum sensing.
An optimized faster region- based cnn for 1d spectrum sensing and signal identification in cluttered rf environments,
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.SP 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
CSRD2025: A Large-Scale Synthetic Radio Dataset for Spectrum Sensing in Wireless Communications
A new open-source simulator and a characterized 200TB, 25M-frame synthetic radio dataset with 100 modulation classes, intended to train AI models for spectrum sensing.