Due to the implementation and performance limitations of centralized learning automatic
modulation classification (CentAMC) method, this paper proposes a decentralized learning …

To deal with the deep learning-based automatic modulation classification (AMC) in the
scenario that the training dataset are distributed over a network without gathering the data at …

Automatic modulation classification (AMC) is a typical technology for identifying different
modulation types, which has been widely applied into various scenarios. Recently, deep …

Automatic modulation classification (AMC) is of crucial importance for realizing wireless
intelligence communications. Many deep learning based models especially convolution …

Automatic modulation classification (AMC) is a key step of signal demodulation that
determines whether the receiver can correctly receive the transmitted signal without prior …

Automatic modulation classification (AMC) is one of the most important technologies of
cognitive radios and ubiquitous internet of things (IoT) cyber–physical systems, and it can be …

Due to the computing capability and memory limitations, it is difficult to apply the traditional
deep learning (DL) models to the edge devices (EDs) for realizing lightweight automatic …

Automatic modulation classification (AMC) is a promising technology for identifying
modulation types, and deep learning (DL)-based AMC is one of its main research directions …

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 …

The deep convolutional neural network has strong representative ability, which can learn
latent information repeatedly from signal samples and improve the accuracy of automatic …