Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Aliasing01:18

Aliasing

128
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
128
Signal and System01:26

Signal and System

642
A signal x(t) is a set of data or a time function representing a variable of interest. Signals typically convey information about a phenomenon, such as atmospheric temperature, humidity, human voice, television images, a dog's bark, or birdsongs. More generally, a signal can be a function of more than one independent variable. For instance, images depend on horizontal and vertical positions and can be regarded as two-dimensional signals. However, this text will focus on one-dimensional...
642
Design Example01:23

Design Example

321
The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
321

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Evaluating Time Occupancy and Time-Scales in Interference Testing with Pulse-Modulated Noise.

IEEE transactions on electromagnetic compatibility·2026
Same author

Assessing Directional Time-Dependent Interference Vulnerabilities in Closed-Box Wireless Systems.

IEEE transactions on electromagnetic compatibility·2025
Same author

The Expected Peak-to-Average Power Ratio of White Gaussian Noise in Sampled I/Q Data.

IEEE transactions on instrumentation and measurement·2025
Same author

Data-driven modeling of noise time series with convolutional generative adversarial networks.

Machine learning: science and technology·2023
Same author

Blind Measurement of Receiver System Noise.

IEEE transactions on microwave theory and techniques·2020
Same author

Host variables confound gut microbiota studies of human disease.

Nature·2020
Same journal

Precise Numerical Differentiation of Thermodynamic Functions with Multicomplex Variables.

Journal of research of the National Institute of Standards and Technology·2024
Same journal

Characterization of 3-Dimensional Printing and Casting Materials for use in Computed Tomography and X-ray Imaging Phantoms.

Journal of research of the National Institute of Standards and Technology·2024
Same journal

On The Quotient of a Centralized and a Non-centralized Complex Gaussian Random Variable.

Journal of research of the National Institute of Standards and Technology·2024
Same journal

Fast Methods for Finding Multiple Effective Influencers in Real Networks.

Journal of research of the National Institute of Standards and Technology·2024
Same journal

Disinfection of Respirators with Ultraviolet Radiation.

Journal of research of the National Institute of Standards and Technology·2024
Same journal

DNA Origami Design: A How-To Tutorial.

Journal of research of the National Institute of Standards and Technology·2024
See all related articles

Related Experiment Video

Updated: Jun 18, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.0K

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

Jack Sklar1, Adam Wunderlich1

  • 1Communications Technology Laboratory, National Institute of Standards and Technology, Boulder, CO 80305, USA.

Journal of Research of the National Institute of Standards and Technology
|July 31, 2024
PubMed
Summary
This summary is machine-generated.

Generative adversarial networks (GANs) can synthesize realistic radio frequency (RF) signals for spectrum sharing research. This study explores GANs for generating orthogonal frequency-division multiplexing (OFDM) signals, showing promise for data-driven RF signal modeling.

Keywords:
RF data setsgenerative adversarial network (GAN)machine-learningtime series

More Related Videos

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

9.9K
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

5.6K

Related Experiment Videos

Last Updated: Jun 18, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.0K
Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

9.9K
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

5.6K

Area of Science:

  • Electrical Engineering
  • Computer Science
  • Machine Learning

Background:

  • High-quality radio frequency (RF) emission data is crucial for developing spectrum-sharing technologies.
  • Collecting and sharing RF data is challenging due to cost, time, and data restrictions.
  • Accurate RF emission modeling from first principles is difficult due to unknown system parameters.

Purpose of the Study:

  • To investigate the use of generative adversarial networks (GANs) for synthesizing RF communication signals.
  • To evaluate the signal fidelity of GANs trained on baseband orthogonal frequency-division multiplexing (OFDM) signals.
  • To provide a foundation for data-driven methods in RF signal generation.

Main Methods:

  • Developed two novel GAN models for RF signal generation.
  • Trained GANs on baseband OFDM signals modulated with quadrature amplitude modulation (QAM).
  • Evaluated model performance using simulated data sets with varying complexity and fading conditions.

Main Results:

  • Demonstrated the feasibility of using GANs to generate high-fidelity RF signals.
  • Analyzed GAN performance across different OFDM parameters and channel conditions.
  • Identified key factors influencing the accuracy of generated signals.

Conclusions:

  • GANs offer a promising data-driven approach to overcome limitations in RF data collection.
  • The developed GAN models provide a foundation for future research in deep generative models for RF signals.
  • Findings inform the practical application of GANs in spectrum sensing and interference testing.