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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/100/13985

Title: Blind Adaptive Weighted Aggregation Scheme for Event Detection in Multihop Wireless Sensor Networks
Authors: JAGYASI, BG
CHANDER, D
DESAI, UB
MERCHANT, SN
DEY, BK
Keywords: DISTRIBUTED DETECTION
MULTIPLE SENSORS
DECISION FUSION
Issue Date: 2011
Publisher: WILEY-BLACKWELL
Citation: WIRELESS PERSONAL COMMUNICATIONS,58(3)581-597
Abstract: 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.
URI: http://dx.doi.org/10.1007/s11277-010-0123-4
http://dspace.library.iitb.ac.in/jspui/handle/100/13985
ISSN: 0929-6212
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