A comprehensive survey on radio frequency (RF) fingerprinting: Traditional approaches, deep learning, and open challenges
Fifth generation (5G) network and beyond envision massive Internet of Things (IoT) rollout to
support disruptive applications such as extended reality (XR), augmented/virtual reality …
support disruptive applications such as extended reality (XR), augmented/virtual reality …
Machine learning for wireless communications in the Internet of Things: A comprehensive survey
Abstract The Internet of Things (IoT) is expected to require more effective and efficient
wireless communications than ever before. For this reason, techniques such as spectrum …
wireless communications than ever before. For this reason, techniques such as spectrum …
Automatic modulation classification using CNN-LSTM based dual-stream structure
Z Zhang, H Luo, C Wang, C Gan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Deep learning (DL) has recently aroused substantial concern due to its successful
implementations in many fields. Currently, there are few studies on the applications of DL in …
implementations in many fields. Currently, there are few studies on the applications of DL in …
End-to-end learning from spectrum data: A deep learning approach for wireless signal identification in spectrum monitoring applications
This paper presents end-to-end learning from spectrum data-an umbrella term for new
sophisticated wireless signal identification approaches in spectrum monitoring applications …
sophisticated wireless signal identification approaches in spectrum monitoring applications …
ORACLE: Optimized radio classification through convolutional neural networks
K Sankhe, M Belgiovine, F Zhou… - … -IEEE Conference on …, 2019 - ieeexplore.ieee.org
This paper describes the architecture and performance of ORACLE, an approach for
detecting a unique radio from a large pool of bit-similar devices (same hardware, protocol …
detecting a unique radio from a large pool of bit-similar devices (same hardware, protocol …
No Radio Left Behind: Radio Fingerprinting Through Deep Learning of Physical-Layer Hardware Impairments
K Sankhe, M Belgiovine, F Zhou… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
Due to the unprecedented scale of the Internet of Things, designing scalable, accurate,
energy-efficient and tamper-proof authentication mechanisms has now become more …
energy-efficient and tamper-proof authentication mechanisms has now become more …
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 …
A survey on machine learning-based performance improvement of wireless networks: PHY, MAC and network layer
This paper presents a systematic and comprehensive survey that reviews the latest research
efforts focused on machine learning (ML) based performance improvement of wireless …
efforts focused on machine learning (ML) based performance improvement of wireless …
Shared spectrum monitoring using deep learning
Shared spectrum usage is inevitable due to the ongoing increase in wireless services and
bandwidth requirements. Spectrum monitoring is a key enabler for efficient spectrum sharing …
bandwidth requirements. Spectrum monitoring is a key enabler for efficient spectrum sharing …
A comprehensive survey on machine learning approaches for dynamic spectrum access in cognitive radio networks
Due to exponential growth in demand for radio spectrum for wireless communication
networking, the radio spectrum has become over-crowded. The fixed spectrum allocation …
networking, the radio spectrum has become over-crowded. The fixed spectrum allocation …