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Found 6 papers, 1 papers with code
Encoder-Decoder Networks for Self-Supervised Pretraining and Downstream Signal Bandwidth Regression on Digital Antenna Arrays
This work presents the first applications of self-supervised learning applied to data from digital antenna arrays.
Wideband Signal Localization with Spectral Segmentation
We define the signal localization task, present the metrics of precision and recall, and establish baselines for traditional energy detection on this task.
A Wideband Signal Recognition Dataset
Signal recognition is a spectrum sensing problem that jointly requires detection, localization in time and frequency, and classification.
Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks
Channel modeling is a critical topic when considering designing, learning, or evaluating the performance of any communications system.
Physical Layer Communications System Design Over-the-Air Using Adversarial Networks
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 require an analytic model of the impairments in the channel.
Semi-Supervised Radio Signal Identification
Radio emitter recognition in dense multi-user environments is an important tool for optimizing spectrum utilization, identifying and minimizing interference, and enforcing spectrum policy.
