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2015 | OriginalPaper | Chapter

8. Automatic Classification of Digitally Modulated Signals Based on K-Nearest Neighbor

Authors : Woo-Hyun Ahn, Sun-Phil Nah, Bo-Seok Seo

Published in: Future Information Technology - II

Publisher: Springer Netherlands

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Abstract

In this paper, we propose an automatic classification method for eight digitally modulated signals, such as 2FSK, 4FSK, MSK, BPSK, QPSK, 8PSK, 16QAM, and 64QAM. The method uses spectral correlation density and high-order cumulants as features. For feature classification, K-nearest neighbor algorithm is used. Simulation results are demonstrated to evaluate the proposed scheme.

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Metadata
Title
Automatic Classification of Digitally Modulated Signals Based on K-Nearest Neighbor
Authors
Woo-Hyun Ahn
Sun-Phil Nah
Bo-Seok Seo
Copyright Year
2015
Publisher
Springer Netherlands
Book
Future Information Technology - II

Print ISBN: 978-94-017-9557-9

Electronic ISBN: 978-94-017-9558-6

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-94-017-9558-6_8