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) plays a key role in non-cooperative
communication systems. Feature-based (FB) methods have been widely studied in …

Automatic signal recognition (ASR) plays an important role in various applications such as
dynamic spectrum access and cognitive radio, hence it will be a key enabler for beyond 5G …

In recent years, neural network algorithms have demonstrated tremendous potential for
modulation classification. Deep learning methods typically take raw signals or convert …

In signal communication based on a non-cooperative communication system, the receiver is
an unlicensed third-party communication terminal, and the modulation parameters of the …

Multi‐function radars (MFRs) are sophisticated sensors with fine‐grained modes, which
modify their modulation types and parameters range generating various signals to fulfil …

Automatic modulation recognition (AMR) is becoming more important because it is usable in
advanced general-purpose communication such as, cognitive radio, as well as, specific …

Automatic modulation recognition (AMR) is a critical technology in spatial cognitive radio
(SCR), and building high-performance AMR model can achieve high classification accuracy …

This article analyses the possibility of using the Analytic Wavelet Transform (AWT) and the
Convolutional Neural Network (CNN) for the purpose of recognizing the intrapulse …

Automatic modulation discrimination (AMC) is one of the critical technologies in spatial
cognitive communication systems. Building a high-performance AMC model in intelligent …