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


In this paper, we address the problem of distributed detection of a non-cooperative (unknown emitted signal) target with a Wireless Sensor Network (WSN). When the target is present, sensors observe an (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 (IoT), one-bit sensor measurement quantization is employed and two strategies for quantization are investigated. The Fusion Center (FC) receives sensor bits via noisy Binary Symmetric Channels (BSCs) and provides a more accurate global inference. Such a model leads to a test with nuisances (i.e. the target position xT) observable only under H1 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. Simulation results confirm the promising performance of our proposed approaches.

Original languageEnglish (US)
JournalIEEE Internet of Things Journal
StateAccepted/In press - 2021


  • Distributed detection
  • Fading channels
  • Generalized Likelihood Ratio Test
  • Internet of Things
  • Internet of Things (IoT)
  • Locally-Optimum Detection (LOD)
  • Probability density function
  • Quantization (signal)
  • Rao test
  • Sensors
  • Signal to noise ratio
  • Wireless sensor networks
  • Wireless Sensor Networks (WSNs).

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'Distributed Detection in Wireless Sensor Networks under Multiplicative Fading via Generalized Score-tests'. Together they form a unique fingerprint.

Cite this