A comprehensive survey on radio frequency (RF) fingerprinting: Traditional approaches, deep learning, and open challenges

A Jagannath, J Jagannath, PSPV Kumar - Computer Networks, 2022‏ - Elsevier
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 …

Machine learning for wireless communications in the Internet of Things: A comprehensive survey

J Jagannath, N Polosky, A Jagannath, F Restuccia… - Ad Hoc Networks, 2019‏ - Elsevier
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 …

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 …

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 …

End-to-end learning from spectrum data: A deep learning approach for wireless signal identification in spectrum monitoring applications

M Kulin, T Kazaz, I Moerman, E De Poorter - IEEE access, 2018‏ - ieeexplore.ieee.org
This paper presents end-to-end learning from spectrum data-an umbrella term for new
sophisticated wireless signal identification approaches in spectrum monitoring applications …

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 …

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 …

Shared spectrum monitoring using deep learning

FA Bhatti, MJ Khan, A Selim… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
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 …

A survey on machine learning-based performance improvement of wireless networks: PHY, MAC and network layer

M Kulin, T Kazaz, E De Poorter, I Moerman - Electronics, 2021‏ - mdpi.com
This paper presents a systematic and comprehensive survey that reviews the latest research
efforts focused on machine learning (ML) based performance improvement of wireless …

Sums: Sniffing unknown multiband signals under low sampling rates

J Peng, Z Chen, Z Lin, H Yuan, Z Fang… - IEEE Transactions …, 2024‏ - ieeexplore.ieee.org
Due to sophisticated deployments of all kinds of wireless networks (eg, 5G, Wi-Fi, Bluetooth,
LEO satellite, etc.), multiband signals distribute in a large bandwidth (eg, from 70 MHz to 8 …