Text-Guided Diffusion Models for Robust RF Signal Generation (DiffusionRF)

Diffusion models have shown remarkable success in generating high-quality synthetic data in image, text, and audio modalities, but have not yet been explored in the RF domain. Unlike the image domain, RF signals present a challenging and complex environment that can be characterized by varying time-varying propagation effects, multipath fading, interference from overlapping signals, and diverse modulation schemes, all of which create dynamic and nonlinear behavior across different frequencies and time scales. These challenges create a unique opportunity to extend the capabilities of diffusion models to generate synthetic RF data for both congested and contested environments including Electronic Warfare (EW) applications, where the complexity of RF environments requires more sophisticated data generation techniques. Nexcepta proposes to design and develop the Text-Guided Diffusion Models for Robust RF Signal Generation (DiffusionRF) technology.