Generating Noise-like Communication Codes with Deep Learning

Author(s):

Michael S Lee

Abstract:

Communication with a low-probability of detection can help prevent targeted jamming and transmitter geolocation. In this report, we use a generative-adversarial network to design symbol communication codes that appear as Gaussian white noise, which is the idealized analogue of expected RF background and thermal circuit noise.