Automatic modulation classification (AMC) plays an important role in both civilian and
military applications. Today, increasingly more researchers apply a deep learning …

Deep learning (DL) has been recognized as an effective solution for automatic modulation
classification (AMC). However, most recent DL based AMC works are based on real-valued …

As a backbone of deep learning models, convolutional neural networks (CNNs) are widely
used in the field of automatic modulation classification. Nevertheless, we speculate that the …

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 (AMC) has been studied for more than a quarter of a
century; however, it has been difficult to design a classifier that operates successfully under …

Automatic modulation classification (AMC) is an promising technology for non-cooperative
communication systems in both military and civilian scenarios. Recently, deep learning (DL) …

Automatic modulation classification (AMC) identifies a received signal's modulation scheme
without prior knowledge of the intercepted signal, which enables significant applications in …

Automatic modulation classification (AMC) is to identify the modulation type of a received
signal, which plays a vital role to ensure the physical-layer security for Internet of Things …

Automatic modulation classification (AMC) is a key step of signal demodulation that
determines whether the receiver can correctly receive the transmitted signal without prior …

Deep learning has great potential for automatic modulation classification (AMC). However,
its performance largely hinges upon the availability of sufficient high-quality labeled data. In …