Optimal fusion rule for distributed detection in clustered wireless sensor networks

Aldalahmeh, Sami A., Ghogho, Mounir, McLernon, Des and Nurellari, Edmond (2016) Optimal fusion rule for distributed detection in clustered wireless sensor networks. EURASIP Journal on Advances in Signal Processing, 2016 (1). p. 5. ISSN 1687-6172

Full content URL: http://dx.doi.org/10.1186/s13634-016-0303-9

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We consider distributed detection in a clustered wireless sensor network (WSN) deployed randomly in a large field for the purpose of intrusion detection. The WSN is modeled by a homogeneous Poisson point process. The sensor nodes (SNs) compute local decisions about the intruder’s presence and send them to the cluster heads (CHs). A stochastic geometry framework is employed to derive the optimal cluster-based fusion rule (OCR), which is a weighted average of the local decision sum of each cluster. Interestingly, this structure reduces the effect of false alarm on the detection performance. Moreover, a generalized likelihood ratio test (GLRT) for cluster-based fusion (GCR) is developed to handle the case of unknown intruder’s parameters. Simulation results show that the OCR performance is close to the Chair-Varshney rule. In fact, the latter benchmark can be reached by forming more clusters in the network without increasing the SN deployment intensity. Simulation results also show that the GCR performs very closely to the OCR when the number of clusters is large enough. The performance is further improved when the SN deployment intensity is increased.

Keywords:wireless sensor network, Cluster, Distributed detection, Fusion rule, Stochastic geometry, JCOpen
Subjects:H Engineering > H641 Telecommunications Engineering
H Engineering > H600 Electronic and Electrical Engineering
H Engineering > H640 Communications Engineering
Divisions:College of Science > School of Engineering
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ID Code:27391
Deposited On:21 Jun 2017 08:14

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