NAS-AMR: Neural architecture search-based automatic modulation recognition for integrated sensing and communication systems

X Zhang, H Zhao, H Zhu, B Adebisi… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Automatic modulation recognition (AMR) technique plays an important role in the
identification of modulation types of unknown signal of integrated sensing and …

A survey of blind modulation classification techniques for OFDM signals

A Kumar, S Majhi, G Gui, HC Wu, C Yuen - Sensors, 2022 - mdpi.com
Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent
transceiver for future wireless communications. Blind MC has several applications in the …

Automatic modulation classification using deep residual neural network with masked modeling for wireless communications

Y Peng, L Guo, J Yan, M Tao, X Fu, Y Lin, G Gui - Drones, 2023 - mdpi.com
Automatic modulation classification (AMC) is a signal processing technology used to identify
the modulation type of unknown signals without prior information such as modulation …

Texture-aware self-attention model for hyperspectral tree species classification

N Li, S Jiang, J Xue, S Ye, S Jia - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Forests play an irreplaceable role in carbon sinks. However, there are obvious differences in
the carbon sink capacity of different tree species, so the scientific and accurate identification …

A semi-supervised modulation identification in MIMO systems: A deep learning strategy

S Bouchenak, R Merzougui, F Harrou, A Dairi… - IEEE …, 2022 - ieeexplore.ieee.org
Accurate modulation identification of the received signals is undoubtedly a central
component in multiple-input multiple-output (MIMO) communication systems, facilitating the …

Research on Video Quality Diagnosis System Based on Convolutional Neural Network

Y Hu, X Zhan - International Journal of Informatics and Information …, 2023 - ijiis.org
In the era of rapid development in modern society, there is an escalating demand for high-
performance products. However, this quest for excellence often encounters persistent quality …

Discriminating WirelessHART Communication Devices Using Sub-Nyquist Stimulated Responses

JD Long, MA Temple, CM Rondeau - Electronics, 2023 - mdpi.com
Reliable detection of counterfeit electronic, electrical, and electromechanical devices within
critical information and communications technology systems ensures that operational …

Deep Learning-Based Modulation Recognition for Low Signal-to-Noise Ratio Environments

P He, Y Zhang, X Yang, X Xiao, H Wang, R Zhang - Electronics, 2022 - mdpi.com
Automatic modulation classification (AMC), which plays a significant role in wireless
communication, can recognize the modulation type of the received signal without large …

Supervised Contrastive Learning‐Based Modulation Classification of Underwater Acoustic Communication

D Gao, W Hua, W Su, Z Xu… - … and Mobile Computing, 2022 - Wiley Online Library
Modulation parameters are very significant to underwater target recognition. But influenced
by the severe and time‐space varying channel, most currently proposed intelligent …

Deep multilevel architecture for automatic modulation classification

A Parmar, A Chouhan, K Captain, J Patel - Physical Communication, 2024 - Elsevier
In the realm of wireless communication, deep learning has exhibited promising outcomes
across various tasks, including automatic modulation classification (AMC), channel …