Abstract

In this study Automatic Modulation Classification (AMC) which is based on cyclostationary property of the modulated signal are discussed and implemented for the purpose of classification. Modulation Classification (MC) is a technique used to make better the overall performance of cognitive radios. Recently Cognitive Radio (CR) plays a key role in the field of communication. CR also used in the development of different wireless application and the exploitation of civilian and military applications. In modulated signals there is cyclostationary property that can be used for the detection of modulation formats. The extraction of cyclostationary features, is used for classification of digital modulation schemes at different values of SNR’s.

Keywords:

Automatic Modulation Classification (AMCs), Cyclic Domain Profile (CDP), cyclostationary features, Cognitive Radio (CR), Feed Forward Back Propagation Neural Network (FFBPNN), Spectral Coherence Function (SCF),

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Competing interests

The authors have no competing interests.

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