Automatic modulation recognition is a rapidly evolving area of signal analysis. In recent
years, interest from the academic and military research institutes has focused around the …

The automatic recognition of the modulation format of a detected signal, the intermediate
step between signal detection and demodulation, is a major task of an intelligent receiver …

A simple method, based on elementary fourth-order cumulants, is proposed for the
classification of digital modulation schemes. These statistics are natural in this setting as …

We apply the maximum-likelihood (ML) method to the classification of digital quadrature
modulations. We show that under an ideal situation, the IQ domain data are sufficient …

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 …

This paper presents a method for the automatic classification of digital modulations without a
priori knowledge of the signal parameters. This method can recognize classical single …

In non-cooperative communication scenarios, automatic modulation classification (AMC) is
the premise of information acquisition. It has been a difficult issue for decades due to the …

This paper presents a comparative study of implementation of feature extraction and
classification algorithms based on discrete wavelet decompositions and Adaptive Network …

Recently, due to the wide application of low probability of intercept (LPI) radar, lots of
recognition approaches about LPI radar signal modulations have been proposed. However …

In recent times, spectrum sensing and spectrum management become a crucial design
issue in cognitive radio networks (CRN). To improve the spectrum utilization in CRN, the …