The demand for bandwidth-critical applications has stimulated the research community not
only to develop new ways of communication, but also to use the existing spectrum efficiently …

Due to the implementation and performance limitations of centralized learning automatic
modulation classification (CentAMC) method, this paper proposes a decentralized learning …

The process of automatic classification of a detected signal's employed modulation type has
gained importance in recent years. The goal of such an approach is to maximize the …

Automatic modulation classification (AMC) is an important technology in military signal
reconnaissance and civilian communications such as cognitive radios. Most of the existing …

The Automatic Modulation Classification (AMC) of the underwater acoustic communication
signals is still difficult via traditional methods in the case of poor underwater acoustic …

Recently, deep learning models have been widely applied to modulation recognition, and
they have become a hot topic due to their excellent end-to-end learning capabilities …

It is a challenge for automatic modulation recognition (AMR) methods for radiation source
signals to work in environments with low signal-to-noise ratios (SNRs). This paper proposes …

Spectrum awareness techniques have been proposed as a promising solution to improve
the utilization of available spectrum bands. However, few works have discussed the …

Aiming at the limitations of traditional communication modulation recognition algorithms, a
novel recognition algorithm based on deep learning network far communication signal …

In this paper, we present a novel constellation-based detection algorithm designed to
identify frequency spread OFDM underlay signals in dynamic and complex wireless …