DocumentCode :
1855045
Title :
A simple and robust modulation classification method via counting
Author :
Huo, Xiaoming ; Donoho, David
Author_Institution :
Dept. of Stat., Stanford Univ., CA, USA
Volume :
6
fYear :
1998
fDate :
12-15 May 1998
Firstpage :
3289
Abstract :
Automatic modulation classification (or recognition) is an intrinsically interesting problem with a variety of regulatory and military applications. We developed a method which is simple, fast, efficient and robust. The feature being used is the counts of signals falling into different parts of the signal plane. Compared with the likelihood method and the high order correlation method, it is much easier to be implemented, and the execution is much faster. When the channel model is correct, our method is efficient, in the sense that it will achieve the “optimal” classification rate. When unknown contamination is present, our method can automatically overcome it to certain degree. At SNRs of 10 and 15 dB, examples of classifying two modulation types-QAM4 and PSK6-are given. Simulations demonstrate its ability to deal with unknown noise
Keywords :
pattern classification; phase shift keying; quadrature amplitude modulation; 10 dB; 15 dB; PSK6; QAM4; SNR; automatic modulation classification; automatic modulation recognition; channel model; counting; efficient method; high order correlation method; likelihood method; military application; modulation classification method; noise; optimal classification rate; regulatory applications; robust method; signal plane; simulations; Additive noise; Contamination; Correlation; Gaussian noise; Geometry; Magnetohydrodynamics; Noise robustness; Partitioning algorithms; Signal to noise ratio; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
ISSN :
1520-6149
Print_ISBN :
0-7803-4428-6
Type :
conf
DOI :
10.1109/ICASSP.1998.679567
Filename :
679567
Link To Document :
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