Journal ArticleDOI
Shared Spectrum Monitoring using Deep Learning
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TLDR
A novel (spectrogram) representation called the Quarter-spectrogram (Q-Spectrogram) that squeezes temporal and frequency information for input to CNN models and a simple WiFi classification scheme that buffers several WiFi Q-spectrograms and then makes a decision about WiFi’s presence and also gives a quantified measure of WiFi traffic density.Citations
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MR-DCAE: Manifold regularization-based deep convolutional autoencoder for unauthorized broadcasting identification
TL;DR: The manifold regularization‐based deep convolutional autoencoder (MR‐DCAE) model for unauthorized broadcasting identification is introduced and it can be observed that the expert knowledge hidden in normal signals can be extracted and emphasized, rather than simple overfitting.
Journal ArticleDOI
Deep learning based automatic modulation recognition: Models, datasets, and challenges
TL;DR: In this article , the authors present a review of the state-of-the-art DL-AMR approaches for single-input-single-output (SISO) systems from both accuracy and complexity perspectives.
Journal ArticleDOI
Radar Deception Jamming Recognition Based on Weighted Ensemble CNN With Transfer Learning
TL;DR: Wang et al. as mentioned in this paper proposed a weighted ensemble CNN with transfer learning (WECNN-TL)-based radar active deception jamming recognition algorithm to obtain the time-frequency distribution maps of jamming signals by the short-time Fourier transform (STFT), and then, their real parts, imaginary parts, moduli, and phases are combined differently to construct multiple datasets.
Proceedings ArticleDOI
Spectrum Activity Monitoring and Analysis for Sub-6 GHz Bands Using a Helikite
Sung Joon Maeng,Özgür Özdemir,H. N. Nandakumar,Ismail Güvenç,Mihail L. Sichitiu,Rudra Dutta,Magreth Mushi +6 more
TL;DR: In this article , the authors report sub-6 GHz spectrum measurement results at multiple ground fixed nodes and a helikite flying at altitudes up to 500 feet at the NSF AERPAW platform in Raleigh, NC.
Journal ArticleDOI
A Multiscale CNN Framework for Wireless Technique Classification in Internet of Things
TL;DR: A multiscale convolutional neural network framework is proposed for wireless technique classification that can achieve a better classification performance and a higher convergence speed compared to the state-of-the-art schemes.