Wireless signal recognition plays an important role in cognitive radio, which promises a
broad prospect in spectrum monitoring and management with the coming applications for …

Since the emergence of 5G technology, the wireless communication system has had a huge
data throughput, so the joint development of artificial intelligence technology and wireless …

Modulation classification is one of the key tasks for communications systems monitoring,
management, and control for addressing technical issues, including spectrum awareness …

Deep learning (DL) is a new machine learning (ML) methodology that has found successful
implementations in many application domains. However, its usage in communications …

This paper proposes a convolutional neural network (CNN), called SCGNet, for low-
complexity and robust modulation recognition in intelligent communication receivers …

In this paper, we review a variety of deep learning algorithms and models for modulation
recognition and classification of wireless communication signals. Specifically, deep learning …

Automatic modulation classification (AMC) aims at identifying the modulation format of the
received signal. In this letter, we propose a novel grid constellation matrix (GCM)-based …

Deep learning has been widely exploited in radio modulation recognition in recent years. In
this paper, we exploit empirical mode decomposition (EMD) and variational mode …

Automatic modulation classification (AMC) is an important stage in intelligent wireless
communication receivers. It is a necessary process after signal detection, and before …

Modulation recognition plays an indispensable role in the field of wireless communications.
In this paper, a novel attention cooperative framework based on deep learning is proposed …