Automatic modulation classification in impulsive noise: Hyperbolic-tangent cyclic spectrum and multibranch attention shuffle network

J Ma, M Hu, T Wang, Z Yang, L Wan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Automatic modulation classification plays an essential role in cognitive communication
systems. Traditional automatic modulation classification approaches are primarily …

Super-resolution time delay estimation using exponential kernel correlation in impulsive noise and multipath environments

J Ma, J Zhang, Z Yang, H Liu, L Wan, T Qiu - Digital Signal Processing, 2023 - Elsevier
The time delay estimation (TDE) is an important and fundamental part in wireless
communication signal processing, which has been widely used in localization, intelligent …

Time and phase features network model for automatic modulation classification

T Cui, D Wang, L Ji, J Han, Z Huang - Computers and Electrical …, 2023 - Elsevier
Abstract Automatic Modulation Classification (AMC) constitutes a fundamental technology
for enabling automatic demodulation in Cognitive Communication Systems (CCS). Due to …

Attention-based adversarial robust distillation in radio signal classifications for low-power IoT devices

L Zhang, S Lambotharan, G Zheng… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
Due to great success of transformers in many applications, such as natural language
processing and computer vision, transformers have been successfully applied in automatic …

Automatic modulation classification: Decision tree based on error entropy and global-local feature-coupling network under mixed noise and fading channels

S Luan, Y Gao, W Chen, N Yu… - IEEE Wireless …, 2022 - ieeexplore.ieee.org
A decision tree structure is proposed to handle automatic modulation classification under
mixed noise and fading channels. In the first layer of the tree, IQ signals are categorized into …

MobileRaT: A Lightweight Radio Transformer Method for Automatic Modulation Classification in Drone Communication Systems

Q Zheng, X Tian, Z Yu, Y Ding, A Elhanashi… - Drones, 2023 - mdpi.com
Nowadays, automatic modulation classification (AMC) has become a key component of next-
generation drone communication systems, which are crucial for improving communication …

Complex-valued parallel convolutional recurrent neural networks for automatic modulation classification

Y Ren, W Jiang, Y Liu - 2022 IEEE 25th International …, 2022 - ieeexplore.ieee.org
Following the great success of deep learning in signal processing, Many models based on
real-valued convolutional neural networks (CNNs) and recurrent neural networks (RNNs) …

Multiscale correlation networks based on deep learning for automatic modulation classification

J Xiao, Y Wang, D Zhang, Q Ma… - IEEE Signal Processing …, 2023 - ieeexplore.ieee.org
Automatic Modulation Classification (AMC) is a challenging yet significant technique for
communication systems. Deep learning methods, though widely employed for AMC, are …

Deep multi-scale representation learning with attention for automatic modulation classification

X Wu, S Wei, Y Zhou - 2022 International Joint Conference on …, 2022 - ieeexplore.ieee.org
Currently, deep learning methods with stacking small size convolutional filters are widely
used for automatic modulation classification (AMC). In this report, we find some experienced …

ShuffleFormer: An efficient shuffle meta framework for automatic modulation classification

J Ma, Y Jing, Z Yang, H Yang, Z Wu - Physical Communication, 2023 - Elsevier
Automatic modulation classification (AMC) plays an essential and fundamental part in
wireless communication systems, which can greatly enhance the efficiency of spectrum …