DocumentCode :
3222432
Title :
Multi-receiver modulation classification for satellite communications signals
Author :
Farhang, Mahmoud ; Dehghani, H. ; Bahramgiri, H.
Author_Institution :
Dept. of Electr. & Electron. Eng., Malek-Ashtar Univ. of Technol., Tehran, Iran
fYear :
2011
fDate :
16-18 Nov. 2011
Firstpage :
569
Lastpage :
573
Abstract :
In order to improve the performance of modulation classification systems, the idea of multi-receiver recognition has been developed recently. In this paper multiple receivers´ collaboration at different information levels is investigated for classification of signals used in DVB-S2 standard. Three methods are proposed for receivers´ cooperation at each one of signal, feature and decision levels. The proposed methods use cumulants and MLP neural network as signal features and classifier respectively. These methods are evaluated and compared through performance, complexity and equipment. The results show that receivers´ cooperation at signal level offers more accurate classification compared to feature and decision levels, in addition to less computational complexity.
Keywords :
multilayer perceptrons; pattern recognition; receivers; satellite communication; signal classification; telecommunication computing; DVB-S2 standard; MLP neural network; computational complexity; cumulants; decision level; feature level; multilayer perceptron; multireceiver modulation classification; multireceiver recognition; satellite communications signal; signal classification; signal feature; signal level; AWGN; Artificial neural networks; Computational complexity; Digital video broadcasting; Feature extraction; Modulation; Receivers; DVB-S2; automatic modulation classification; data fusion; multi-receiver;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal and Image Processing Applications (ICSIPA), 2011 IEEE International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4577-0243-3
Type :
conf
DOI :
10.1109/ICSIPA.2011.6144156
Filename :
6144156
Link To Document :
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