Deep learning based automatic modulation recognition: Models, datasets, and challenges
Automatic modulation recognition (AMR) detects the modulation scheme of the received
signals for further signal processing without needing prior information, and provides the …
signals for further signal processing without needing prior information, and provides the …
A survey of modulation classification using deep learning: Signal representation and data preprocessing
Modulation classification is one of the key tasks for communications systems monitoring,
management, and control for addressing technical issues, including spectrum awareness …
management, and control for addressing technical issues, including spectrum awareness …
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 …
development of cognitive radios. It is the cornerstone of adaptive modulation and …
Multitask-learning-based deep neural network for automatic modulation classification
Automatic modulation classification (AMC) is to identify the modulation type of a received
signal, which plays a vital role to ensure the physical-layer security for Internet of Things …
signal, which plays a vital role to ensure the physical-layer security for Internet of Things …
A survey of blind modulation classification techniques for OFDM signals
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 …
transceiver for future wireless communications. Blind MC has several applications in the …
Amcrn: Few-shot learning for automatic modulation classification
Deep learning (DL) has been widely applied in automatic modulation classification (AMC),
while the superb performance highly depends on high-quality datasets. Motivated by this …
while the superb performance highly depends on high-quality datasets. Motivated by this …
Intelligent radio signal processing: A survey
Intelligent signal processing for wireless communications is a vital task in modern wireless
systems, but it faces new challenges because of network heterogeneity, diverse service …
systems, but it faces new challenges because of network heterogeneity, diverse service …
Automatic modulation classification: A deep architecture survey
Automatic modulation classification (AMC), which aims to blindly identify the modulation type
of an incoming signal at the receiver in wireless communication systems, is a fundamental …
of an incoming signal at the receiver in wireless communication systems, is a fundamental …
Signal processing-based deep learning for blind symbol decoding and modulation classification
Blindly decoding a signal requires estimating its unknown transmit parameters,
compensating for the wireless channel impairments, and identifying the modulation type …
compensating for the wireless channel impairments, and identifying the modulation type …
Automatic modulation classification using compressive convolutional neural network
The deep convolutional neural network has strong representative ability, which can learn
latent information repeatedly from signal samples and improve the accuracy of automatic …
latent information repeatedly from signal samples and improve the accuracy of automatic …