Deep learning based automatic modulation recognition: Models, datasets, and challenges

F Zhang, C Luo, J Xu, Y Luo, FC Zheng - Digital Signal Processing, 2022 - Elsevier
Automatic modulation recognition (AMR) detects the modulation scheme of the received
signals for further signal processing without needing prior information, and provides the …

Machine learning based automatic modulation recognition for wireless communications: A comprehensive survey

B Jdid, K Hassan, I Dayoub, WH Lim, M Mokayef - IEEE Access, 2021 - ieeexplore.ieee.org
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 …

Big data analysis of the internet of things in the digital twins of smart city based on deep learning

X Li, H Liu, W Wang, Y Zheng, H Lv, Z Lv - Future Generation Computer …, 2022 - Elsevier
The study aims to conduct big data analysis (BDA) on the massive data generated in the
smart city Internet of things (IoT), make the smart city change to the direction of fine …

[HTML][HTML] Large-scale real-world radio signal recognition with deep learning

TU Ya, LIN Yun, ZHA Haoran, J Zhang, W Yu… - Chinese Journal of …, 2022 - Elsevier
In the past ten years, many high-quality datasets have been released to support the rapid
development of deep learning in the fields of computer vision, voice, and natural language …

Deep learning for security in digital twins of cooperative intelligent transportation systems

Z Lv, Y Li, H Feng, H Lv - IEEE transactions on intelligent …, 2021 - ieeexplore.ieee.org
The purpose is to solve the security problems of the Cooperative Intelligent Transportation
System (CITS) Digital Twins (DTs) in the Deep Learning (DL) environment. The DL algorithm …

Contour stella image and deep learning for signal recognition in the physical layer

Y Lin, Y Tu, Z Dou, L Chen… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The rapid development of communication systems poses unprecedented challenges, eg,
handling exploding wireless signals in a real-time and fine-grained manner. Recent …

An efficient specific emitter identification method based on complex-valued neural networks and network compression

Y Wang, G Gui, H Gacanin, T Ohtsuki… - IEEE Journal on …, 2021 - ieeexplore.ieee.org
Specific emitter identification (SEI) is a promising technology to discriminate the individual
emitter and enhance the security of various wireless communication systems. SEI is …

A novel intrusion detection method based on lightweight neural network for internet of things

R Zhao, G Gui, Z Xue, J Yin, T Ohtsuki… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The purpose of a network intrusion detection (NID) is to detect intrusions in the network,
which plays a critical role in ensuring the security of the Internet of Things (IoT). Recently …

Deep learning-based smart predictive evaluation for interactive multimedia-enabled smart healthcare

Z Lv, Z Yu, S **e, A Alamri - ACM Transactions on Multimedia Computing …, 2022 - dl.acm.org
Two-dimensional arrays of bi-component structures made of cobalt and permalloy elliptical
dots with thickness of 25 nm, length 1 mm and width of 225 nm, have been prepared by a …

DL-PR: Generalized automatic modulation classification method based on deep learning with priori regularization

Q Zheng, X Tian, Z Yu, H Wang, A Elhanashi… - … Applications of Artificial …, 2023 - Elsevier
Automatic modulation classification (AMC) is an essential and indispensable topic in the
development of cognitive radios. It is the cornerstone of adaptive modulation and …