Publications

Displaying 1 - 3 of 3

Data-Driven Modeling of Noise Time Series with Convolutional Generative Adversarial Networks

August 21, 2023

Author(s)

Adam Wunderlich, Jack Sklar

Random noise arising from physical processes is an inherent characteristic of measurements and a limiting factor for most signal processing and data analysis tasks. Given the recent interest in generative adversarial networks (GANs) for data-driven

Feasibility of Modeling Orthogonal Frequency-Division Multiplexing Communication Signals with Unsupervised Generative Adversarial Networks

February 14, 2022

Author(s)

Jack Sklar, Adam Wunderlich

High-quality recordings of radio frequency (RF) emissions from commercial communication hardware in realistic environments are often needed to develop and assess spectrum-sharing technologies and practices, e.g., for training and testing spectrum sensing

AWS-3 LTE Impacts on Aeronautical Mobile Telemetry

February 25, 2021

Author(s)

William F. Young, Duncan McGillivray, Adam Wunderlich, Mark Krangle, Jack Sklar, Aric Sanders, Keith Forsyth, Mark A. Lofquist, Dan Kuester

This technical report details an effort to design, demonstrate, and validate a test methodology to measure the impacts of Long Term Evolution (LTE) User Equipment (UE) emissions in the advanced wireless services 3 (AWS-3) band on aeronautical mobile

Search Publications by: