n-west/Wideband-RF-Signal-Detection-with-Machine-Learning

This is a tutorial of ML for people with a DSP/wireless background to do Wideband Spectrum Detection. If you are interested in working in this space see deepsig.ai.

See the paper "A Wideband Signal Recognition Dataset" at SPAWC 2021 and https://eval.ai/web/challenges/challenge-page/1057/.

If you use this please cite one of the following

Examples

@inproceedings{west:wideband-tutorial,
  author =       {West, Nathan and Wagoner, Amy},
  title =        {Wideband RF Signal Detection with Machine Learning},
  booktitle =    {GNU Radio Conference},
  year      = 2021,
  publisher = "GNU Radio TPC"
}

Dataset

@inproceedings{west:wideband-dataset,
  author =       {West, Nathan and O'Shea Timothy and Roy, Tamoghna},
  title =        {A Wideband Signal Recognition Dataset},
  booktitle =    {Proceedings of 2021 IEEE Conference on Signal Processing for Wireless Communications},
  year      = 2021,
  publisher = "IEEE"
}

Spectral segmentation / IOU metrics / Dataset

@inproceedings{west:wideband-signal-localization,
  author =       {West, Nathan and Roy, Tamoghna and O'Shea Timothy},
  title =        {Wideband Signal Localization with Spectral Segmentation},
  booktitle =    {Proceedings of 2020 Asilomar Conference on Signals, Systems, and Computers},
  year      = 2020,
  publisher = "IEEE"
}