Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33093
The Performance Improvement of Automatic Modulation Recognition Using Simple Feature Manipulation, Analysis of the HOS, and Voted Decision
Authors: Heroe Wijanto, Sugihartono, Suhartono Tjondronegoro, Kuspriyanto
Abstract:
The use of High Order Statistics (HOS) analysis is expected to provide so many candidates of features that can be selected for pattern recognition. More candidates of the feature can be extracted using simple manipulation through a specific mathematical function prior to the HOS analysis. Feature extraction method using HOS analysis combined with Difference to the Nth-Power manipulation has been examined in application for Automatic Modulation Recognition (AMR) to perform scheme recognition of three digital modulation signal, i.e. QPSK-16QAM-64QAM in the AWGN transmission channel. The simulation results is reported when the analysis of HOS up to order-12 and the manipulation of Difference to the Nth-Power up to N = 4. The obtained accuracy rate of AMR using the method of Simple Decision obtained 90% in SNR > 10 dB in its classifier, while using the method of Voted Decision is 96% in SNR > 2 dB.Keywords: modulation, automatic modulation recognition, feature analysis, feature manipulation.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058025
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2119References:
[1] E. E. Azzouz, A. K. Nandi, Automatic Modulation Recognition of Communication Signals (Boston- Dordrecht-London, Kluwer Academic Publisher, 2003).
[2] A. Ebrahimzadeh, M. Ardebilipour, & A. Movahedian, Automatic Digital Signal Types Recognition Using SI-NN and HOS, Advanced Topics in Signal Processing, Proc. IEEE Conf. on ICC, 2007.
[3] A. Ebrahimzadeh, S. A. Seyedin, & M. Dehghan, Digital-Signal-Type Identification Using an Efficient Identifier, EURASIP Journal on Advances in Signal Processing, Vol. 2007, Article ID 37690.
[4] Jie Li, Jun Wang, Xiaoyan Fan, & Yi Zhang, Automatic Digital Modulation Recognition Using Feature Subset Selection, Proc. Progress in Electromagnetics Research Symp., Hangzhou, China, March 24-28, 2008
[5] O. A. Dobre, Y. Bar-Ness, & Wei Su, Higher-Order Cyclic Cumulants for High Order Modulation Classification, Proc. IEEE Conf. on MILCOM, 2003.
[6] O. A. Dobre, Y. Bar-Ness, & Wei Su, Robust QAM Modulation Classification Algorithm Using Cyclic Cumulants, Proc. IEEE Conf. on WCNC, 2004.