Modulation signal classification in communication systems can be considered a pattern
recognition problem. Earlier works have focused on several feature extraction approaches …

Identifying the modulation type of radio signals is challenging in both military and civilian
applications such as radio monitoring and spectrum allocation. This has become more …

Light is a type of electromagnetic wave. Research on the modulation recognition of
communication signals, which are also electromagnetic waves, can be applied to the field of …

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

This study proposes robust convolutional neural network (CNN)-based automatic
modulation classification (AMC) techniques. Traditional AMCs may be classified into two …

In this paper, we demonstrate a software defined radio (SDR) prototype with the capability of
signal classification in real-time. Detection, classification, and characterization of wireless …

Deep learning has recently been used for this issue with superior results in automatic
modulation classification. Previous studies state that it is challenging to categorize a variety …

Automatic modulation recognition (AMR) is one of the essential parts in the intelligent
communication system. In the underwater acoustic communication, it is a challenging work …

Implementation of Automatic modulation classification originated in the military field several
years ago. Threat analysis, surveillance, and welfare where of great concern, thus this urged …

In general, CNN gives the same weight to all position information, which will limit the
expression ability of the model. Distinguishing modulation types that are significantly …