The development of wireless communication technology has led to the underutilization of
radio spectra. To address this limitation, an intelligent cognitive radio network was …

Advances in communication technology have enabled SMC to be widely used in non-
cooperative identification situations such as spectrum detection, electronic …

We present an automatic signal modulation classification model using combinatorial deep
learning technique. Our proposed deep learning model increase accuracy for low Signal-to …

Automatic modulation classification is a desired feature in many modern software-defined
radios; however, classification performance degrades with decreasing signal to noise ratios …

Automatic Modulation Classi ication (AMC) is a well‑known problem in the Radio Frequency
(RF) domain. Solv‑ing this problem requires determining the modulation of an RF signal …

With the evolutionary development of modern communications technology, automatic
modulation classification (AMC) has played an increasing role in the complex wireless …

In this paper, we propose an effective feature-based automatic modulation classification
(AMC) method using a deep neural network (DNN). In order to classify the modulation type …

In non-cooperative communication scenarios, automatic modulation classification (AMC) is
the premise of information acquisition. It has been a difficult issue for decades due to the …

In this work, we investigate the feasibility and effectiveness of employing deep learning
algorithms for automatic recognition of the modulation type of received wireless …

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