Distributed classification under statistical dependence with application to automatic modulation classification

Hao He, Sora Choi, Pramod Kumar Varshney, Wei Su

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

Abstract

In this paper, we consider the distributed classification of discrete random signals in wireless sensor networks (WSNs). Observing the same random signal makes sensors' observations conditionally dependent which complicates the design of distributed classification systems. In the literature, this dependence has been ignored for simplicity although this may significantly affect the performance of the classification system. We derive the necessary conditions for the optimal decision rules at the sensors and the fusion center (FC) by introducing a 'hidden' random variable. Furthermore, we introduce an iterative algorithm to search for the optimal decision rules. The proposed scheme is applied to a distributed Automatic Modulation Classification (AMC) problem. It is shown to attain superior performance in comparison with other approaches which disregard the inter-sensor dependence.

Original languageEnglish (US)
Title of host publication2015 18th International Conference on Information Fusion, Fusion 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1597-1602
Number of pages6
ISBN (Print)9780982443866
StatePublished - Sep 14 2015
Event18th International Conference on Information Fusion, Fusion 2015 - Washington, United States
Duration: Jul 6 2015Jul 9 2015

Other

Other18th International Conference on Information Fusion, Fusion 2015
CountryUnited States
CityWashington
Period7/6/157/9/15

Keywords

  • automatic modulation classification
  • dependent observations
  • distributed classification
  • wireless sensor networks

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing
  • Computer Networks and Communications

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  • Cite this

    He, H., Choi, S., Varshney, P. K., & Su, W. (2015). Distributed classification under statistical dependence with application to automatic modulation classification. In 2015 18th International Conference on Information Fusion, Fusion 2015 (pp. 1597-1602). [7266747] Institute of Electrical and Electronics Engineers Inc..