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Higher-order cyclic cumulants for high order modulation classification

Authors: O.A. Dobre; Y. Bar-Ness; null Wei Su;

Higher-order cyclic cumulants for high order modulation classification

Abstract

In this paper we investigate automatic modulation classification (AMC) using homogeneous feature-vectors based on cyclic cumulants (CCs) of fourth-, sixth- and eight-orders, respectively, for QAM, PSK and ASK signals within a pattern recognition framework. Analysis of CCs of the baseband signal at the receiver is performed and used for feature selection. The cycle spectrum of the baseband signal at the receiver is derived as a function of excess bandwidth for a raised cosine pulse shape and a necessary and sufficient condition on the oversampling factor is obtained. Theoretical arguments regarding the discrimination capability of the examined feature-vectors are verified through extensive simulations.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
153
Top 1%
Top 1%
Top 10%
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