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Deep Generative Modeling for Communication Systems Testing and Data Sharing


This project aims to develop deep generative models, an emerging topic in AI, for radio frequency (RF) waveforms collected from real-world communications hardware.  After initial investigations with simulated datasets, we plan to develop generative models using real datasets collected by Communication Technology Labratories (CTL). Potential applications of this work include generation of waveforms for interference testing, characterization of black-box communication systems, and signal obfuscation for data sharing.

potential Applications:

  • Generate waveforms for interference testing
  • Characterize emissions from “black box” systems
  • Obfuscate sensitive waveform attributes for data sharing
Created March 23, 2021