Distributed detection over connected networks via one-bit quantizer

Shengyu Zhu, Biao Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

This paper considers distributed detection over large scale connected networks with arbitrary topology. Contrasting to the canonical parallel fusion network where a single node has access to the outputs from all other sensors, each node can only exchange one-bit information with its direct neighbors in the present setting. Our approach adopts a novel consensus reaching algorithm using asymmetric bounded quantizers that allow controllable consensus error. Under the Neyman-Pearson criterion, we show that, with each sensor employing an identical one-bit quantizer for local information exchange, this approach achieves the optimal error exponent of centralized detection provided that the algorithm converges. Simulations show that the algorithm converges when the network is large enough.

Original languageEnglish (US)
Title of host publicationProceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1526-1530
Number of pages5
Volume2016-August
ISBN (Electronic)9781509018062
DOIs
StatePublished - Aug 10 2016
Event2016 IEEE International Symposium on Information Theory, ISIT 2016 - Barcelona, Spain
Duration: Jul 10 2016Jul 15 2016

Other

Other2016 IEEE International Symposium on Information Theory, ISIT 2016
CountrySpain
CityBarcelona
Period7/10/167/15/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Distributed detection over connected networks via one-bit quantizer'. Together they form a unique fingerprint.

  • Cite this

    Zhu, S., & Chen, B. (2016). Distributed detection over connected networks via one-bit quantizer. In Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory (Vol. 2016-August, pp. 1526-1530). [7541554] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2016.7541554