In this paper, we propose low-complexity binarized deep belief network (DBN) based deep
learning approach along with noise resilient spectral correlation function as a feature …

Automated Modulation Classification (AMC) has been applied in various emerging areas
such as cognitive radio (CR). In our paper, we propose a deep learning-based AMC method …

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

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 …

This paper introduces a new technique for automatic modulation classification (AMC) in
Cognitive Radio (CR) networks. The method employs a straightforward classifier that utilizes …

Automatic modulation categorization (AMC) is used in many applications such as cognitive
radio, adaptive communication, electronic reconnaissance, and non-cooperative …

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

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) …

Addressing the spectrum scarcity problem under the explosive growth of wireless network
applications and data traffic, requires a decidedly global research focus on Cognitive Radio …