The rapid development of information and wireless communication technologies together
with the large increase in the number of end-users have made the radio spectrum more …

This paper proposes a convolutional neural network (CNN), called SCGNet, for low-
complexity and robust modulation recognition in intelligent communication receivers …

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 …

Automatic modulation classification plays an essential role in cognitive communication
systems. Traditional automatic modulation classification approaches are primarily …

Automatic modulation recognition (AMR) has become increasingly important in the field of
signal processing, especially with the advancements of intelligent communication systems …

Modulation recognition is the indispensable part of signal interception analysis, which has
always been the research hotspot in the field of radio communication. With the increasing …

Specific emitter identification (SEI) and automatic modulation classification (AMC) are
generally two separate tasks in the field of radio monitoring. Both tasks have similarities in …

Blind modulation classification is an important step in implementing cognitive radio
networks. The multiple-input multiple-output (MIMO) technique is widely used in military and …

In recent years, automatic modulation classification (AMC) has proved its importance for the
military as well as civil applications and deep learning (DL) based AMC has attracted wide …

In this paper, we present a comprehensive survey and detailed comparison of techniques
that have been applied to the problem of identifying the type of modulation contained within …