An effective algorithm for automatic modulation recognition

Author

Ghasemi, Saleh ; Gangal, Ali

Author_Institution

Elektrik-Elektron. Muhendisligi Bolumu, Karadeniz Teknik Univ., Trabzon, Turkey

fYear

2014

fDate

23-25 April 2014

Firstpage

903

Lastpage

906

Abstract

Based on the previous studies, this article proposes an effective modulation recognition algorithm which is a combination of Higher Order Cumulants (HOC) and Continues Wavelet Transform (CWT). In the Additive White Gaussian Noise (AWGN) the identification of QAM16, QAM32, QAM64, BPSK, QPSK and PSK8 types of modulation were almost successful. In the case of the signal-to-noise ratio (SNR) was higher than -7dB, the identification of QAM16, QAM32 and QAM64 modulation types were 100% successful. While SNR was higher than -2dB, BPSK, QPSK and PSK8 modulation types were identified with success percentage of 100%, 98% and 99%, respectively.

Keywords

AWGN; higher order statistics; phase shift keying; quadrature amplitude modulation; wavelet transforms; AWGN; BPSK modulation; CWT; HOC; PSK8 modulation; QAM16 modulation; QAM32 modulation; QAM64 modulation; QPSK modulation; additive white Gaussian noise; automatic modulation recognition; continues wavelet transform; higher order cumulants; signal- to-noise ratio; Binary phase shift keying; Conferences; Quadrature amplitude modulation; Transforms; automatic digital modulation recognition; continuous wavelet transform; higher order cumulants; multilayer neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications Applications Conference (SIU), 2014 22nd

Conference_Location

Trabzon

Type

conf

DOI

10.1109/SIU.2014.6830376

Filename

6830376