Public Data Resource

Software and Data for Modeling OFDM Communication Signals with Generative Adversarial Networks

Contact: Jack Sklar.
Identifier: doi:10.18434/mds2-2428
Version: 1.0...

There is a more recent release of this resource available:    1.4.0

This repository contains Python code and data for experiments on generative modeling of synthetic Orthogonal-Frequency Division Multiplexing (OFDM) communication signals. The code implements two novel Generative adversarial network (GAN) models, PSK-GAN and STFT-GAN, as well as the WaveGAN model architecture as a baseline for comparison. See README.pdf located in research_software.tar for an overview of the files and instructions for getting started with the software.
Research Areas
NIST R&D: Mathematics and Statistics: Image and signal processingAdvanced Communications: Wireless (RF)
Keywords: generative adversarial networkmachine learningwireless communications
These data are public.
Files

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Version: 1.0...

There is a more recent release of this resource available:    1.4.0

Cite this dataset
Jack Sklar (2021), Software and Data for Modeling OFDM Communication Signals with Generative Adversarial Networks, National Institute of Standards and Technology, https://doi.org/10.18434/mds2-2428 (Accessed 2025-02-14)
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