Title :
Identification of Wavelet Modulation Signals Based on Time-Frequency Mixed Moment
Author :
Tang, Xianghong ; Li, Liyue ; Zhao, Ling ; Li, Shuangxia
Author_Institution :
Sch. of Commun. Eng., Hangzhou Dianzi Univ., Hangzhou, China
Abstract :
Wavelet modulation (WM) signal is a special kind of multi-carrier modulation signals (MCMS). Based on the time-frequency characteristics of WM signal, this paper use the mixed moments of the adaptive optimal kernel (AOK) time-frequency distribution to study the identification of multi-carrier modulation signals. Simulation results show that, this method can separate wavelet modulation signal from OFDM signal, also it can identify wavelet modulation signals of different levels.
Keywords :
OFDM modulation; signal processing; wavelet transforms; OFDM signal; adaptive optimal kernel time-frequency distribution; multicarrier modulation signals; time-frequency mixed moment; wavelet modulation signals; Feature extraction; Kernel; OFDM modulation; Signal analysis; Signal generators; Signal processing; Signal to noise ratio; Time frequency analysis; Wavelet domain; Wavelet transforms; Wavelet modulation; adaptive optimal kernel; time-frequency distribution; time-frequency mixed moments;
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
DOI :
10.1109/AICI.2009.71
