Distributed Detection in Wireless Sensor Networks under Multiplicative Fading via Generalized Score Tests

Domenico Ciuonzo, Pierluigi Salvo Rossi, Pramod K. Varshney

Research output: Contribution to journalArticlepeer-review

73 Scopus citations


In this article, we address the problem of distributed detection of a noncooperative (unknown emitted signal) target with a wireless sensor network. When the target is present, sensors observe a (unknown) deterministic signal with attenuation depending on the unknown distance between the sensor and the target, multiplicative fading, and additive Gaussian noise. To model energy-constrained operations within Internet of Things, one-bit sensor measurement quantization is employed and two strategies for quantization are investigated. The fusion center receives sensor bits via noisy binary symmetric channels and provides a more accurate global inference. Such a model leads to a test with nuisances (i.e., the target position $\boldsymbol {x}_{T}$ ) observable only under $\mathcal {H}_{1}$ hypothesis. Davies' framework is exploited herein to design the generalized forms of Rao and locally optimum detection (LOD) tests. For our generalized Rao and LOD approaches, a heuristic approach for threshold optimization is also proposed. The simulation results confirm the promising performance of our proposed approaches.

Original languageEnglish (US)
Article number9344705
Pages (from-to)9059-9071
Number of pages13
JournalIEEE Internet of Things Journal
Issue number11
StatePublished - Jun 1 2021
Externally publishedYes


  • Distributed detection (DD)
  • Internet of Things (IoT)
  • Rao test
  • generalized-likelihood ratio test
  • locally optimum detection (LOD)
  • wireless sensor networks (WSNs)

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications


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