A survey on deep learning techniques in wireless signal recognition
X Li, F Dong, S Zhang, W Guo - Wireless Communications and …, 2019 - Wiley Online Library
Wireless signal recognition plays an important role in cognitive radio, which promises a
broad prospect in spectrum monitoring and management with the coming applications for …
broad prospect in spectrum monitoring and management with the coming applications for …
Over-the-air deep learning based radio signal classification
We conduct an in depth study on the performance of deep learning based radio signal
classification for radio communications signals. We consider a rigorous baseline method …
classification for radio communications signals. We consider a rigorous baseline method …
An introduction to deep learning for the physical layer
We present and discuss several novel applications of deep learning for the physical layer.
By interpreting a communications system as an autoencoder, we develop a fundamental …
By interpreting a communications system as an autoencoder, we develop a fundamental …
Performance of feature-based techniques for automatic digital modulation recognition and classification—A review
The demand for bandwidth-critical applications has stimulated the research community not
only to develop new ways of communication, but also to use the existing spectrum efficiently …
only to develop new ways of communication, but also to use the existing spectrum efficiently …
Automatic determination of digital modulation types with different noises using convolutional neural network based on time–frequency information
In this study, a novel digital modulation classification model has been proposed for
automatically recognizing six different modulation types including amplitude shift keying …
automatically recognizing six different modulation types including amplitude shift keying …
SigNet: A novel deep learning framework for radio signal classification
Deep learning methods achieve great success in many areas due to their powerful feature
extraction capabilities and end-to-end training mechanism, and recently they are also …
extraction capabilities and end-to-end training mechanism, and recently they are also …
Automatic modulation classification of digital modulation signals with stacked autoencoders
A Ali, F Yangyu, S Liu - Digital Signal Processing, 2017 - Elsevier
Modulation identification of the transmitted signals remain a challenging area in modern
intelligent communication systems like cognitive radios. The computation of the distinct …
intelligent communication systems like cognitive radios. The computation of the distinct …
A survey of traditional and advanced automatic modulation classification techniques, challenges, and some novel trends
Automatic modulation classification (AMC) is an important stage in intelligent wireless
communication receivers. It is a necessary process after signal detection, and before …
communication receivers. It is a necessary process after signal detection, and before …
Communication without interception: Defense against modulation detection
We consider a communication scenario, in which an intruder tries to determine the
modulation scheme of the intercepted signal. Our aim is to minimize the accuracy of the …
modulation scheme of the intercepted signal. Our aim is to minimize the accuracy of the …
The best defense is a good offense: Adversarial attacks to avoid modulation detection
We consider a communication scenario, in which an intruder tries to determine the
modulation scheme of the intercepted signal. Our aim is to minimize the accuracy of the …
modulation scheme of the intercepted signal. Our aim is to minimize the accuracy of the …