Likelihood function-based modulation classification in bandwidth- constrained sensor networks

Jefferson L. Xu, Wei Su, Mengchu Zhou

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

10 Scopus citations

Abstract

Automatic modulation classification with a single receiver has been intensively studied for two decades. Enhancing the successful classification probability is a bottleneck in this research field especially with weak signals in a non-cooperative communication environment. A sensor network with distributed classification techniques is expected to achieve technology breakthrough in providing spatial diversity and increasing the classification reliability. In this paper, we developed a distributed likelihood function-based classification method and extend the automatic modulation classification to sensor or radio networks. The classification methods performed in the sensors and primary node associated with theoretical discussion and numerical results are presented.

Original languageEnglish (US)
Title of host publication2010 International Conference on Networking, Sensing and Control, ICNSC 2010
Pages530-533
Number of pages4
DOIs
StatePublished - Jun 9 2010
Event2010 International Conference on Networking, Sensing and Control, ICNSC 2010 - Chicago, IL, United States
Duration: Apr 10 2010Apr 12 2010

Publication series

Name2010 International Conference on Networking, Sensing and Control, ICNSC 2010

Other

Other2010 International Conference on Networking, Sensing and Control, ICNSC 2010
CountryUnited States
CityChicago, IL
Period4/10/104/12/10

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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