Automatic modulation classification (AMC) is an essential technique in intelligent receivers
of non-cooperative communication systems such as cognitive radio networks and military …

Automatic modulation classification for radio signals is an important task in many
applications, including cognitive radio, radio spectrum monitoring and signal decoding in …

The arrival of 5G has accelerated the development of the Internet of things and vehicular
technology, which often need to transmit large amounts of data through wireless networks …

With rapid advancement in artificial intelligence (AI) and machine learning (ML), automatic
modulation classification (AMC) using deep learning (DL) techniques has become very …

Automatic modulation classification (AMC) aims to identify the modulation format of the
received signals corrupted by the noise, which plays a major role in radio monitoring. In this …

With the rapid emergence of advanced technologies for wireless communications, automatic
modulation classification (AMC) has been deployed in the physical layer to blindly identify …

In this paper, a low-feedback-sampling-rate digital predistortion (DPD) method is proposed
for wideband wireless transmitters and radio-frequency power amplifiers (PAs). This DPD …

Automatic Modulation Classification (AMC) is the process of determining the modulation
scheme of an intercepted signal with no a priori information about its characteristics. AMC's …

In this paper, we propose low-complexity binarized deep belief network (DBN) based deep
learning approach along with noise resilient spectral correlation function as a feature …

In this paper, we investigate the demodulation performance of radar-embedded
communications, by utilizing deep neural network (DNN) machine learning to extract the …