Algorithm for automatic recognition of PSK and QAM with unique classifier based on features and threshold levels
作者： Ahmed K. Ali , Ergun Erçelebi
DOI: 10.1016/J.ISATRA.2020.03.002
关键词:
摘要: In this paper, we present a unique modulation classification method that is based on determining an attractive relation between higher-order cumulants (HOCs) using decision tree-classifier to improve the extracted features employed for recognition of schemes, such as phase shift keying (PSK) and quadrature amplitude (QAM). A threshold algorithm applied proposed classifier, which consists sub-classifiers, each comprising single feature, being capable distinguishing types individually. work, high-accuracy classifier system utilized recognize QAM (16, 32, 64, 128, 256) (2, 4, 8) PSK at low signal-to-noise ratio (SNR). study, 1000 signals are studied SNR -5 dB 30 dB. The most prominent results decisions range from 88% 100% with regard same QAM. long run, module will be advantageous in terms accuracy computational complexity relative other classifiers literature. demonstrate has significantly better comparison previously ones.
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