Distributed Binary Quantizers for Communication Constrained Large-scale Sensor Networks

Abstract

We consider in this paper local sensor quantizer design for large-scale bandwidth and/or energy constrained wireless sensor networks (WSNs) operating in fading channels. In particular, under the Neyman-Pearson framework, we address the de- sign of binary local sensor quantizers for a binary hypothesis problem in the asymptotic regime where the number of sensors is large. Motivated by the sensor censoring idea for reduced communication rate, each sensor either transmits "1" to a fusion center or remains silent. By adopting energy detector as the fusion rule, we develop a procedure to obtain local sensor threshold that maximizes the Kullback-Leibler distance of the distributions of the fusion statistic under the two hypotheses. The proposed quantizer design is well suited for the emerging large scale resource-constrained WSNs applications. Numerical results based on Gaussian and exponential observations are presented to demonstrate the design procedure.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2006
Accession Number
ADA524577

Entities

People

  • Biao Chen
  • Bruce Suter
  • Peter Willett
  • Ying Lin

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Detection
  • Detectors
  • False Alarms
  • Gaussian Distributions
  • Gaussian Noise
  • Networks
  • Noise
  • Observation
  • Probability
  • Sensor Networks
  • Simulations
  • Warning Systems
  • Wireless Sensor Networks

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Networking
  • Statistical inference.