Title
Decision fusion using fuzzy threshold scheme for target detection in sensor networks.
Abstract
Spectrum sensing is a fundamental surveillance task and is used to detect target signal. Energy detection is a popular spectrum sensing technique. But detection performance of energy detector deteriorates in low signal-to-noise ratio (SNR) conditions and under noise uncertainty. In this paper, we proposed an energy detector with fuzzy threshold scheme for spectrum sensing, in which each sensor node sends local decision to the fusion center depending on the region in which the observed energy lies. Fusion center then makes a final global decision by combining local decisions. Analysis and simulations show that the proposed fuzzy threshold scheme could improve the detect probability effectively under ‘OR’,‘AND’ and ‘K-out-of-N’ fusion rules, and overcome the confused region problem. Monte Carlo Simulation results also show that proposed scheme achieves better detection performance and outperforms both conventional energy detector of both single and double threshold, respectively.
Year
DOI
Venue
2018
10.1016/j.jocs.2017.08.017
Journal of Computational Science
Keywords
Field
DocType
Energy detection,Fuzzy logic,Decision fusion
Sensor node,Data mining,Monte Carlo method,Mathematical optimization,Decision fusion,Computer science,Fuzzy logic,Fusion rules,Algorithm,Fusion center,Detector,Wireless sensor network
Journal
Volume
ISSN
Citations 
25
1877-7503
0
PageRank 
References 
Authors
0.34
8
4
Name
Order
Citations
PageRank
Yee Ming Chen1648.33
Chi-Shun Hsueh200.34
Chu-Kai Wang300.68
Tai-Yi Wu400.34