This study proposes robust convolutional neural network (CNN)-based automatic
modulation classification (AMC) techniques. Traditional AMCs may be classified into two …

Automatic modulation classification (AMC) plays an important role in intelligent wireless
communications. With the rapid development of deep learning in recent years, neural …

Deep learning has been widely used in automatic modulation classification (AMC) recently.
Most of deep learning-based AMC uses a single network model to deal with radio signals …

Automatic Modulation Classification (AMC), which based on deep learning has been
extensively researched and implemented in wireless communication systems. Universal …

Automatic modulation classification (AMC) is the demodulation process on the receiver side,
which is a crucial protocol for current and next‐generation intelligent communication …

Modulation recognition is an important technology in wireless communication systems. In
recent years, deep learning-based modulation recognition algorithms, which can …

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 recognition is a major project in the field of radio cognition; however,
the generalization ability of conventional models cannot satisfy practical applications. In …

The electromagnetic environments have become more complex with the development of
wireless communication technology. Signal modulation classification has attracted extensive …

Traditional likelihood-based and handcrafted feature-based methods for overlapped signals
automatic modulation classification (OS-AMC) suffer from the uncertainty of the overlapped …