DocumentCode :
2710530
Title :
A neural network receiver for EM-MWD baseband communication systems
Author :
Whitacre, Timothy ; Yu, Xiao-Hua
Author_Institution :
Dept. of Electr. Eng., California Polytech. State Univ., San Luis Obispo, CA, USA
fYear :
2009
fDate :
14-19 June 2009
Firstpage :
3360
Lastpage :
3364
Abstract :
Baseband digital communication in ldquoelectromagnetic measurement while drillingrdquo systems (EM-MWD) is often corrupted by surface noise. The conventional correlation receiver works well under the assumption of additive white Gaussian noise (AWGN); however in practice, the noise is actually non-stationary and usually contains spectral peaks in lower frequency range. In this research, a new approach based on artificial neural network is investigated. The neural network receiver has adaptive learning ability and outperforms the correlation receiver under various noise conditions, especially in the situation of non-white noise as well as the real world noise taken from actual drilling sites.
Keywords :
AWGN; digital communication; drilling; learning (artificial intelligence); measurement systems; neural nets; production engineering computing; receivers; EM-MWD baseband communication systems; adaptive learning; additive white Gaussian noise; artificial neural network; baseband digital communication; correlation receiver; drilling systems; electromagnetic measurement; neural network receiver; noise conditions; nonwhite noise; spectral peaks; surface noise; AWGN; Adaptive systems; Additive white noise; Artificial neural networks; Baseband; Digital communication; Frequency; Gaussian noise; Neural networks; Noise measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location :
Atlanta, GA
ISSN :
1098-7576
Print_ISBN :
978-1-4244-3548-7
Electronic_ISBN :
1098-7576
Type :
conf
DOI :
10.1109/IJCNN.2009.5178838
Filename :
5178838
Link To Document :
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