Performance analysis for distributed classification fusion using soft-decision decoding in wireless sensor networks

Authors:
Jing-Tian Sung;Hung-Ta Pai;Bih-Hwang Lee
Affiliations:
Dept. of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan;Graduate Institute of Communication Engineering, National Taipei University, Taipei, Taiwan;Dept. of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
Venue:
EUC'07 Proceedings of the 2007 international conference on Embedded and ubiquitous computing
Year:
2007

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Abstract

Distributed Classification Fusion using Error-Correcting Codes (DCFECC) has recently been proposed for wireless sensor networks. It adopts the Minimum Hamming Distance (MHD) fusion rule and performs much better than traditional classification approaches when the network has faulty sensors. Different fusion rules were proposed later. One of them is Distributed Classification fusion using Soft-decision Decoding (DCSD). The DCSD fusion rule has a considerably lower misclassification probability than the MHD fusion rule. This work analyzes the performance of the DCSD fusion rule. Asymptotic performance approximation of the DCSD fusion rule is derived based on the Central Limit Theorem. Furthermore, an asymptotic upper bound on the misclassification probability is obtained. Finally, numerical simulations are conducted to verify our analysis results.