Machine learning based automatic modulation recognition for wireless communications: A comprehensive survey
The rapid development of information and wireless communication technologies together
with the large increase in the number of end-users have made the radio spectrum more …
with the large increase in the number of end-users have made the radio spectrum more …
Multitask-learning-based deep neural network for automatic modulation classification
Automatic modulation classification (AMC) is to identify the modulation type of a received
signal, which plays a vital role to ensure the physical-layer security for Internet of Things …
signal, which plays a vital role to ensure the physical-layer security for Internet of Things …
Evaluating adversarial evasion attacks in the context of wireless communications
B Flowers, RM Buehrer… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Recent advancements in radio frequency machine learning (RFML) have demonstrated the
use of raw in-phase and quadrature (IQ) samples for multiple spectrum sensing tasks. Yet …
use of raw in-phase and quadrature (IQ) samples for multiple spectrum sensing tasks. Yet …
Deep learning-based automated modulation classification for cognitive radio
Automated Modulation Classification (AMC) has been applied in various emerging areas
such as cognitive radio (CR). In our paper, we propose a deep learning-based AMC method …
such as cognitive radio (CR). In our paper, we propose a deep learning-based AMC method …
Automatic modulation classification for cognitive radios using cyclic feature detection
B Ramkumar - IEEE Circuits and Systems Magazine, 2009 - ieeexplore.ieee.org
Cognitive radios have become a key research area in communications over the past few
years. Automatic modulation classification (AMC) is an important component that improves …
years. Automatic modulation classification (AMC) is an important component that improves …
Low complexity automatic modulation classification based on order-statistics
In this paper, we propose three automatic modulation classification classifiers based on
order-statistics and reduced order-statistics, where the order-statistics are the random …
order-statistics and reduced order-statistics, where the order-statistics are the random …
A hierarchical classification head based convolutional gated deep neural network for automatic modulation classification
Automatic modulation classification (AMC) identifies a received signal's modulation scheme
without prior knowledge of the intercepted signal, which enables significant applications in …
without prior knowledge of the intercepted signal, which enables significant applications in …
Cognitive radio and networking research at Virginia Tech
More than a dozen Wireless@ Virginia Tech faculty are working to address the broad
research agenda of cognitive radio and cognitive networks. Our core research team spans …
research agenda of cognitive radio and cognitive networks. Our core research team spans …
On the limitations of targeted adversarial evasion attacks against deep learning enabled modulation recognition
Wireless communications has greatly benefited in recent years from advances in machine
learning. A new subfield, commonly termed Radio Frequency Machine Learning (RFML) …
learning. A new subfield, commonly termed Radio Frequency Machine Learning (RFML) …
Signal detection effects on deep neural networks utilizing raw IQ for modulation classification
SC Hauser, WC Headley… - MILCOM 2017-2017 …, 2017 - ieeexplore.ieee.org
Recently, automatic modulation classification techniques using convolutional neural
networks on raw IQ samples have been investigated and show promise when compared to …
networks on raw IQ samples have been investigated and show promise when compared to …