Resource-Constrained Wireless Sensor Network Information Decision Fusion in Ocean Environment
In order to solve the decision information fusion issues of resource-constrained wireless sensor network, several decision information fusion rules under exponential distribution fading channel are investigated in this paper. At first, optimal likelihood ratio rule is given. The detection performanc...
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Published in | Applied Mechanics and Materials Vol. 433-435; no. Advances in Mechatronics and Control Engineering II; pp. 229 - 232 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Zurich
Trans Tech Publications Ltd
15.10.2013
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Subjects | |
Online Access | Get full text |
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Summary: | In order to solve the decision information fusion issues of resource-constrained wireless sensor network, several decision information fusion rules under exponential distribution fading channel are investigated in this paper. At first, optimal likelihood ratio rule is given. The detection performance of this fusion rule is best, however, this rule acquires channel information which is too costly for resource constrained sensor networks. To solve this problem, suboptimal likelihood ratio fusion rule is proposed which requires only the knowledge of channel statistics. In addition, the reduced forms of the suboptimal are also derived, in the case of extreme channel signal-to-noise ratio (SNR). Theoretical analysis and simulations show that suboptimal fusion rule needs much less computation and information, yet exhibits only slight performance degradation. Suboptimal fusion rules are practicable for resource constrained wireless sensor networks decision information fusion system working in ocean environment. |
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Bibliography: | Selected, peer reviewed papers from the 2013 2nd International Conference on Mechatronics and Control Engineering (ICMCE 2013), August 28-29, 2013, Guangzhou, China ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISBN: | 303785894X 9783037858943 |
ISSN: | 1660-9336 1662-7482 1662-7482 |
DOI: | 10.4028/www.scientific.net/AMM.433-435.229 |