GAN generated models for Signal Integrity, Thermal Modeling, Etc., Center for Advanced Electronics through Machine Learning (CAEML) Core Project 5A3

at NC State University for a given radio frequency.

NC State researchers will develop Conditional Generative Adversarial Networks (GANs) to model radio transmitters and receivers, as well as to predict temperature maps based on a given radio frequency. GANs are a type of machine learning system that learn to generate data that match a training set, in this case, providing detailed models of wireless communication networks and temperature maps. The results of this research will enable wireless engineers to better design and operate wireless networks.