Wireless signal characterization is a growing area of research and an essential tool to
enable spectrum monitoring, tactical signal recognition, spectrum management, signal …

Wireless signal recognition is becoming increasingly more significant for spectrum
monitoring, spectrum management, and secure communications. Consequently, it will …

Future communication networks must address the scarce spectrum to accommodate
extensive growth of heterogeneous wireless devices. Efforts are underway to address …

Recognizing signals is critical for understanding the increasingly crowded wireless spectrum
space in noncooperative communications. Traditional threshold or pattern recognition …

In cognitive radio, signal recognition is an important technology and modulation recognition
plays a key role in it. With the development of artificial intelligence, deep learning algorithms …

Radio signal recognition is a crucial task in both civilian and military applications, as
accurate and timely identification of unknown signals is an essential part of spectrum …

Signal modulation recognition plays a critical role in many fields to identify the modulation
type of wireless signals. Since the deep learning based models have achieved great …

With the increasing popularity of Internet of things (IoT), the emergence of many IoT devices
has led to security vulnerabilities. The classification of wireless signals is very important for …

Specific emitter identification (SEI) and automatic modulation classification (AMC) are
generally two separate tasks in the field of radio monitoring. Both tasks have similarities in …

Modulation classification is a research hot-spot in the field of machine learning and the
knowledge-based systems of wireless communication, involving the identification of different …