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 …
Cognitive radio for vehicular ad hoc networks (CR-VANETs): approaches and challenges
With growing interest in using cognitive radio (CR) technology in wireless communication
systems for vehicles, it is envisioned that future vehicles will be CR-enabled. This paper …
systems for vehicles, it is envisioned that future vehicles will be CR-enabled. This paper …
Micro-UAV detection and classification from RF fingerprints using machine learning techniques
This paper focuses on the detection and classification of micro-unmanned aerial vehicles
(UAVs) using radio frequency (RF) fingerprints of the signals transmitted from the controller …
(UAVs) using radio frequency (RF) fingerprints of the signals transmitted from the controller …
Automatic modulation classification using gated recurrent residual network
The development of the Internet-of-Things (IoT) security is comparatively slower than the
pace of the IoT innovations. The seamless IoT network operates in an untrusted environment …
pace of the IoT innovations. The seamless IoT network operates in an untrusted environment …
An overview of feature-based methods for digital modulation classification
A Hazza, M Shoaib, SA Alshebeili… - 2013 1st international …, 2013 - ieeexplore.ieee.org
This paper presents an overview of feature-based (FB) methods developed for Automatic
classification of digital modulations. Only the most well-known features and classifiers are …
classification of digital modulations. Only the most well-known features and classifiers are …
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 …
Deep learning in digital modulation recognition using high order cumulants
W Xie, S Hu, C Yu, P Zhu, X Peng, J Ouyang - IEEE access, 2019 - ieeexplore.ieee.org
By considering the different cumulant combinations of the 2FSK, 4FSK, 2PSK, 4PSK, 2ASK,
and 4ASK, this paper established new identification parameters to achieve the recognition of …
and 4ASK, this paper established new identification parameters to achieve the recognition of …
Automatic digital modulation recognition based on genetic-algorithm-optimized machine learning models
Recognition of the modulation scheme is the intermediate step between signal detection
and demodulation of the received signal in communication networks. Automatic modulation …
and demodulation of the received signal in communication networks. Automatic modulation …
Signal identification for multiple-antenna wireless systems: Achievements and challenges
YA Eldemerdash, OA Dobre… - … Surveys & Tutorials, 2016 - ieeexplore.ieee.org
Signal identification is an umbrella term for signal processing techniques designed for the
identification of the transmission parameters of unknown or partially known communication …
identification of the transmission parameters of unknown or partially known communication …
Automatic digital modulation classification using extreme learning machine with local binary pattern histogram features
Abstract Discrimination of the Local Binary Pattern (LBP) in the classification of different
digital modulation types was investigated in this study. It has been shown that LBP can be …
digital modulation types was investigated in this study. It has been shown that LBP can be …