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