A distributed and energy-efficient framework for Neyman-Pearson detection of fluctuating signals in large-scale sensor networks

Authors:
Yang Yang;Rick S. Blum;Brian M. Sadler
Affiliations:
Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, PA;Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, PA;Army Research Laboratory, Adelphi, MD
Venue:
IEEE Journal on Selected Areas in Communications - Special issue on simple wireless sensor networking solutions
Year:
2010

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Abstract

To address the challenges inherent to a problem of practical interest - of Neyman-Pearson detection of ftuctuating radar signals using wireless sensor networks, we propose in this paper a distributed and energy-efficient framework. Such framework is scalable with respect to the network size, and is able to greatly reduce the dependence on the central fusion center. It assumes a clustering infrastructure, and addresses signal processing and communications related issues arising from different layers. This framework includes a distributed scheduling protocol and a distributed routing protocol, which enable sensor nodes to make their own decisions about information transmissions, without requiring the knowledge of the network global information. In this framework, energy efficiency manifests itself at different network layers in a distributed fashion, and a balance between the detection performance and the energy efficiency is also attained.