19 citations · 22 across the 4 of their papers we have counts for
6 papers
Encoder-Decoder Networks for Self-Supervised Pretraining and Downstream Signal Bandwidth Regression on Digital Antenna Arrays
Rajib Bhattacharjea, Nathan West
This work presents the first applications of self-supervised learning applied to data from digital antenna arrays. Encoder-decoder networks are pretrained on digital array data to…
A Wideband Signal Recognition Dataset
Nathan West, Timothy O'Shea, Tamoghna Roy
Signal recognition is a spectrum sensing problem that jointly requires detection, localization in time and frequency, and classification. This is a step beyond most spectrum sensin…
Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks
Timothy J. O'Shea, Tamoghna Roy, Nathan West
Channel modeling is a critical topic when considering designing, learning, or evaluating the performance of any communications system. Most prior work in designing or learning new…
Physical Layer Communications System Design Over-the-Air Using Adversarial Networks
Timothy J. O'Shea, Tamoghna Roy, Nathan West +1
This paper presents a novel method for synthesizing new physical layer modulation and coding schemes for communications systems using a learning-based approach which does not requi…
Deep Architectures for Modulation Recognition
Nathan E West, Timothy J. O'Shea
We survey the latest advances in machine learning with deep neural networks by applying them to the task of radio modulation recognition. Results show that radio modulation recogni…
Semi-Supervised Radio Signal Identification
Timothy J. O'Shea, Nathan West, Matthew Vondal +1
Radio emitter recognition in dense multi-user environments is an important tool for optimizing spectrum utilization, identifying and minimizing interference, and enforcing spectrum…