This paper presents an overview of feature-based (FB) methods developed for Automatic
classification of digital modulations. Only the most well-known features and classifiers are …

Automatic modulation classification (AMC) is a critical algorithm for the identification of
modulation types so as to enable more accurate demodulation in the non-cooperative …

Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent
transceiver for future wireless communications. Blind MC has several applications in the …

Automatic modulation classification (AMC) is a key step of signal demodulation that
determines whether the receiver can correctly receive the transmitted signal without prior …

Signal modulation identification (SMI) plays a very important role in orthogonal frequency-
division multiplexing (OFDM) systems. Currently, SMI methods are often implemented via …

Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent
transceiver for future wireless communications. However, till date, only a few works have …

Long-range underwater acoustic communication (LR-UWAC) refers to the peer-to-peer
transmission of messages for distances of tens to hundreds of km. It is a key enabling …

In this paper, a Hierarchical Polynomial (HP) classifier is proposed to automatically classify
M-PSK and M-QAM signals in Additive White Gaussian Noise (AWGN) and slow flat fading …

Automatic modulation classification (AMC) plays a vital role in cognitive radio to improve
spectrum utilization efficiency, however, most of the existing works have focused on single …

In the scenarios of non-cooperative wireless communications, automatic modulation
recognition (AMR) is an indispensable algorithm to recognize various types of signal …