1 citations · 1 across the 4 of their papers we have counts for
4 papers
Discrete-Space Generative AI Pipeline for Semantic Transmission of Signals
Silvija Kokalj-Filipovic, Yagna Kaasaragadda
We introduce Discernment, a semantic communication system that transmits the meaning of physical signals (baseband radio and audio) over a technical channel using GenAI models oper…
A look at adversarial attacks on radio waveforms from discrete latent space
Attanasia Garuso, Silvija Kokalj-Filipovic, Yagna Kaasaragadda
Having designed a VQVAE that maps digital radio waveforms into discrete latent space, and yields a perfectly classifiable reconstruction of the original data, we here analyze the a…
ReFormer: Generating Radio Fakes for Data Augmentation
Yagna Kaasaragadda, Silvija Kokalj-Filipovic
We present ReFormer, a generative AI (GAI) model that can efficiently generate synthetic radio-frequency (RF) data, or RF fakes, statistically similar to the data it was trained on…
Deep-Learned Compression for Radio-Frequency Signal Classification
Armani Rodriguez, Yagna Kaasaragadda, Silvija Kokalj-Filipovic
Next-generation cellular concepts rely on the processing of large quantities of radio-frequency (RF) samples. This includes Radio Access Networks (RAN) connecting the cellular fron…