DocumentCode :
3250387
Title :
A novel modulation recognition technique based on artificial bee colony algorithm in the presence of multipath fading channels
Author :
Ozen, Asli ; Ozturk, Cengizhan
Author_Institution :
Nuh Naci Yazgan Univ., Kayseri, Turkey
fYear :
2013
fDate :
2-4 July 2013
Firstpage :
239
Lastpage :
243
Abstract :
In this paper, a novel automatic modulation recognition (AMR) method has been proposed for classifying of the transmitted signals by observing the received data samples in the presence of additive white Gaussian noise (AWGN) and multipath fading channel. The proposed method (ABC-ANN) is based on artificial neural network (ANN) which is trained by artificial bee colony (ABC) algorithm. Because high order statistics are very interesting features to solve the problem of AMR, the high order cumulants have been employed in the proposed ABC-ANN classifier. ABC algorithm is used in finding the optimal weight set of artificial neural networks for classification and the performance of the proposed ABC-ANN algorithm is compared with the performance of ANN classifier (SCG-ANN) using scaled conjugate gradient learning algorithm. Computer simulation results have demonstrated that the proposed recognizer can reach much better classification accuracy than the SCG-ANN in even 0 dB of signal to noise ratio (SNR) value.
Keywords :
AWGN; conjugate gradient methods; fading channels; learning (artificial intelligence); modulation; neural nets; optimisation; signal classification; telecommunication computing; ABC-ANN method; ANN classifier; AWGN; additive white Gaussian noise; artificial bee colony algorithm; artificial neural network; automatic modulation recognition method; conjugate gradient learning algorithm; modulation recognition technique; multipath fading channel; optimal weight set; transmitted signal classification; Artificial neural networks; Binary phase shift keying; Classification algorithms; Feature extraction; Signal to noise ratio; Training; Automatic modulation recognition; artificial bee colony algorithm; artificial neural networks; high order cumulant;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Telecommunications and Signal Processing (TSP), 2013 36th International Conference on
Conference_Location :
Rome
Print_ISBN :
978-1-4799-0402-0
Type :
conf
DOI :
10.1109/TSP.2013.6613928
Filename :
6613928
Link To Document :
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