Automatic modulation classification (AMC) is a critical algorithm for the identification of
modulation types so as to enable more accurate demodulation in the non-cooperative …

With the proliferation of wireless technologies in vehicular networks, robust automatic
modulation classification (AMC) has become crucial for optimizing spectrum utilization and …

Automatic modulation classification (AMC) becomes more and more important in the
electronic reconnaissance. Recently, lots of researchers focus on deep learning architecture …

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

Modulation classification is a research hot-spot in the field of machine learning and the
knowledge-based systems of wireless communication, involving the identification of different …

Automatic modulation classification (AMC) holds a significant position in physical layer
security, offering an innovative method to enhance the security of data transmission and anti …

Specific emitter identification (SEI) is a technique of identifying individual emitters via unique
characteristics of different emitters. In this paper, we consider a SEI problem with transmitter …

Deep learning methods achieve great success in many areas due to their powerful feature
extraction capabilities and end-to-end training mechanism, and recently they are also …

Deep Neural Networks (DNNs) have achieved remarkable accuracy improvements for
automatic modulation classification. However, the employed networks often have millions of …

In this paper, a multi-scale convolutional neural network-based (MSN) method is proposed
for robust automatic modulation classification (AMC). The classifier directly utilizes in-phase …