Multi-Dimensional Classification Algorithm for Automatic Modulation Recognition - Brossura

Albairat, Ouail

 
9781288326761: Multi-Dimensional Classification Algorithm for Automatic Modulation Recognition

Sinossi

This thesis proposes an approach for modulation classification using existing features in a more efficient way. The Multi-Dimensional Classification Algorithm (MDCA) treats features extracted from signals of interest as elements with irrelevant identities, hence eliminating any dependence of the classifier on any particular feature. This design enables the use of any number of features, and the MDCA algorithm provides the capability to classify modulations in higher dimensions. The use of multiple features requires an equal number of data dimensions, and thus classification in as high a dimensional space as possible can improve final classification results. Finally, the MDCA algorithm uses a relatively small number of simple operations, which leads to a fast processing time. Simulation results for the MDCA algorithm demonstrate good potential. In particular, the MDCA consistently performed well (at SNR levels down to -10dB in some cases) and in identifying more modulation types.

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9781025124766: Multi-Dimensional Classification Algorithm for Automatic Modulation Recognition

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ISBN 10:  1025124766 ISBN 13:  9781025124766
Casa editrice: Hutson Street Press, 2025
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