With the proliferation of wireless technologies in vehicular networks, robust automatic
modulation classification (AMC) has become crucial for optimizing spectrum utilization and …

With the development of deep learning (DL), several fields have ushered in leapfrog
development, such as image classification and natural language processing. Combing the …

Modulation classification has been widely studied in recent years. However, few studies
focus on the performance degradation in multipath fading channels, whose impact is non …

Modulation classification is an essential step of signal processing and has been regularly
applied in the field of tele-communication. Since variations of frequency with respect to time …

Although modulation classification with deep learning has been widely explored, this is
challenging when the training data is limited. In this paper, we meet this challenge by data …

Automatic modulation recognition (AMR) is an essential topic of cognitive radio, which is of
great significance for the analysis of wireless signals and is one of the current research …

Automatic modulation recognition (AMR) plays a vital role in non-cooperative
communication systems, which is an important technological component of blind signal …

Automatic modulation classification (AMC) is a typical pattern classification task that is an
intermediate process between signal detection and demodulation. Deep learning methods …

Artificial intelligence (AI) has emerged as the most promising solution expected to overcome
the high degree of abstraction of radio signals and achieve accurate automatic modulation …

This paper presents a new low-area and low-power Field Programmable Gate Array (FPGA)
implementation of a Radio Frequency (RF) modulation classifier based on the Density …