DocumentCode
188277
Title
Decision Fusion Using Three-Level Censoring Scheme in Sensor Networks under Rician Fading Channels
Author
Shoujun Liu ; Kezhong Liu ; Wei Chen
Author_Institution
Sch. of Inf. Eng., Wuhan Univ. of Technol., Wuhan, China
fYear
2014
fDate
13-15 Oct. 2014
Firstpage
343
Lastpage
348
Abstract
This work considers the problem of decision fusion using the three-level censoring scheme in wireless sensor networks. An optimal fusion rule is derived for the model of Rician fading channel. However, the optimal fusion rule requires instantaneous channel state information (CSI) which may be too costly for resource constrained sensor networks. Hence, a sub-optimal alternative with the knowledge of Rician fading statistics is proposed. To further simplify the fusion rules, two low signal-to-noise approximations are also derived. Performance evaluation confirms that by using the three-level censoring scheme, the goal of energy saving and performance improvement can be achieved. The sub-optimal fusion rule based on channel statistics exhibits only slight performance degradation compared with the optimal fusion rule. In addition, the impact of Rician K-factor on the performance of decision fusion has also been discussed.
Keywords
Rician channels; approximation theory; fading channels; wireless sensor networks; CSI; Rician K-factor; Rician fading channels; Rician fading statistics; channel state information; channel statistics; decision fusion; optimal fusion rule; resource constrained sensor networks; signal-to-noise approximations; suboptimal fusion rule; three level censoring scheme; wireless sensor networks; Approximation methods; Error probability; Fading; Rician channels; Signal to noise ratio; Wireless communication; Wireless sensor networks; Rician fading; censoring; decision fusion; wireless sensor networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2014 International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4799-6235-8
Type
conf
DOI
10.1109/CyberC.2014.66
Filename
6984330
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