Performance evaluation of censoring-enabled systems for sequential detection in large wireless sensor networks

Performance evaluation of censoring-enabled systems for sequential detection in large wireless sensor networks

Department

Electronics & Communications Engineering Department

Description

In this paper, we consider a sequential binary hypothesis testing framework in wireless sensor networks. We study the effect of sensor censoring on network performance in terms of the average error probability and average number of observations required until a global decision is made. The detection process is mathematically modeled as a random walk process with two absorbing barriers. We resort to Chernoff bound in order to find upper bounds on the error probabilities and the average stopping time. The main contribution of this paper is to prove that in a sequential binary hypothesis network where sensors send their hard decisions to the fusion center, censoring can enhance the network performance in comparison to non-censoring networks in certain SNR regimes. Numerical evaluation is provided to illustrate the gains achieved through censoring. © 2014 IFIP.

Publication Date

1-1-2014

Document Type

Book Chapter

Book Title

2014 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2014

ISBN

SCOPUS_ID:84904976520

Publisher

IEEE

City

Hammamet, Tunisia

First Page

92

Last Page

98

Performance evaluation of censoring-enabled systems for sequential detection in large wireless sensor networks
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