Automatic modulation classification (AMC) used in cognitive radio networks is an important
class of methods apt to utilize spectrum resources efficiently. However, conventional …

In this paper, a novel deep learning-based robust automatic modulation classification (AMC)
method is proposed for cognitive radio networks. Generally, as network input of AMC …

Automatic modulation classification (AMC) is one of the major challenges for cognitive radio
(CR), which can enhance the spectrum utilization efficiency. In this study, a hybrid signal and …

Automatic modulation classification (AMC) plays a key role in cognitive radio. For AMC,
convolutional neural networks (CNNs) have been explored in previous works extensively …

Automatic modulation classification (AMC) is an essential technique in intelligent receivers
of non-cooperative communication systems such as cognitive radio networks and military …

This letter proposes a cost-efficient convolutional neural network (CNN) for robust automatic
modulation classification (AMC) deployed for cognitive radio services of modern …

Automatic Modulation Classification (AMC) is a critical issue in electromagnetic spatial
perception. Currently traditional recognition techniques are difficult to adapt to complex …

Automatic modulation recognition (AMR) is an essential and challenging topic in the
development of the cognitive radio (CR), and it is a cornerstone of CR adaptive modulation …

Automatic modulation classification (AMC) lies at the core of cognitive radio and spectrum
sensing. In this Letter, the authors propose a novel convolutional neural network (CNN) …

Cognitive radio networks' evolution hinges significantly on the use of automatic modulation
classification (AMC). However, existing research reveals limitations in attaining high AMC …