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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
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 …
ORACLE: Optimized radio classification through convolutional neural networks
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 …
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 …
No Radio Left Behind: Radio Fingerprinting Through Deep Learning of Physical-Layer Hardware Impairments
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
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 …
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 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 …
Sums: Sniffing unknown multiband signals under low sampling rates
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 …
LEO satellite, etc.), multiband signals distribute in a large bandwidth (eg, from 70 MHz to 8 …