A method of quadrature amplitude modulation signals identification at low signal-to-noise ratios

Author

Boyang Feng ; Qingbo Ji ; Yun Lin

Author_Institution

Coll. of Inf. & Commun. Eng., Harbin Eng. Univ., Harbin, China

fYear

2014

fDate

26-29 July 2014

Firstpage

814

Lastpage

817

Abstract

Quadrature Amplitude Modulation (M-QAM) was developed to rapidly and automatically identify the modulation levels of digitally modulated signals at low signal-to-noise ratios (SNR). The method uses wavelet transforms with the optimal scale combining with manifold learning method to identify the modulation levels of the M-QAM signals. Simulation results show that when the SNR is not lower than - 22 dB, the percentage of correct identification of M-QAM is higher than 90%. The results show that the method can rapidly acquire good performance at low SNR.

Keywords

learning (artificial intelligence); quadrature amplitude modulation; signal processing; wavelet transforms; M-QAM signals; SNR; digitally modulated signals; low signal-to-noise ratios; manifold learning method; quadrature amplitude modulation signals identification; wavelet transforms; Feature extraction; Manifolds; Modulation; Signal to noise ratio; Simulation; Wavelet transforms; Isomap; digital modulation; manifold learning; signal identification; wavelet transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Antennas and Propagation (APCAP), 2014 3rd Asia-Pacific Conference on

Conference_Location

Harbin

Print_ISBN

978-1-4799-4355-5

Type

conf

DOI

10.1109/APCAP.2014.6992623

Filename

6992623