Recently, contrastive learning (CL) has exhibited considerable advantages for automatic
modulation classification (AMC) with a scarcity of labeled samples. Nevertheless, the …

Automatic modulation classification (AMC) plays an increasingly crucial role in intelligent
spectrum management and dynamic spectrum access, which can effectively support the …

With the advancement of cognitive radio technology (CRT) in radio communication
networks, deep learning (DL) has become instrumental in enhancing spectrum efficiency …

Signal detection and modulation classification are two crucial tasks in various wireless
communication systems. Different from prior works that investigate them independently, this …

In this study, the modulation of symbols on OFDM subcarriers is classified for transmissions
following Wi-Fi 6 and 5G downlink specifications. First, our approach estimates the OFDM …

In the realm of wireless communication, deep learning has exhibited promising outcomes
across various tasks, including automatic modulation classification (AMC), channel …

Automatic modulation recognition plays a crucial role in the domain of electromagnetic
situational awareness. Early recognition methods predominantly relied on expert experience …

Modulation types clustering (MC) is crucial for adaptive high-frequency communication
between devices in the Industrial Internet of Things. The strength of MC resides in its self …

Automatic modulation recognition (AMR) using deep learning (DL) techniques has attracted
great interest in radio and spectrum management. However, as most signals in practical …

Transfer learning (TL) techniques have proven useful in a wide variety of applications
traditionally dominated by machine learning (ML), such as natural language processing …