Blind adaptive weighted aggregation scheme for event detection in multihop wireless sensor networks

Jagyasi, B G and Chander, D and Desai, U B and Merchant, S N and Dey, B K (2011) Blind adaptive weighted aggregation scheme for event detection in multihop wireless sensor networks. Wireless Personal Communications, 58 (3). pp. 581-597. ISSN 0929-6212

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The problem of decision fusion for event detection in Wireless Sensor Networks is the prime focus of this paper. Our proposed algorithm focuses on single hop (star) and multihop (tree) topologies, which are commonly deployed wireless sensor network topologies. In order to minimize the overall energy consumption in the network, a transmission constraint of one-bit is imposed on each sensor node. This poses a challenging problem of designing a one-bit decision fusion rule at every fusion center, which improves the overall detection accuracy at the sink node. The absence of apriori knowledge of each sensor's local performance indices, makes the existing optimum fusion rule infeasible. Moreover, in the absence of a training sequence of true event occurrences, existing Adaptive distributed detection techniques also become inapplicable. In this setup, the key contribution of this paper is a Least Mean Squares based Blind Adaptive Weighted Aggregation Scheme (Blind-AdWAS) for Wireless Sensor Networks with tree topology. We extend our earlier work (Jagyasi et al. in Proceedings of 11th international symposium on wireless personal multimedia communication, 2008) to include an analysis of the effect of Rayleigh flat fading channel on Blind-AdWAS in comparison with existing channel-aware optimum and sub- optimum aggregation schemes. Even in the absence of any channel knowledge or knowledge of performance indices, Blind-AdWAS demonstrates robustness in event detection performance.

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Item Type: Article
Uncontrolled Keywords: Adaptive aggregation; Distributed detection; Sensor network
Subjects: Physics > Electricity and electronics
Divisions: Department of Electrical Engineering
Depositing User: Team Library
Date Deposited: 03 Nov 2014 06:15
Last Modified: 16 Apr 2015 06:10
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