Predictive behavior classification for cognitive radio: Introduction and preliminary results

Daniel DePoy, Tamal Bose

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

2 Scopus citations

Abstract

Cognitive Radio systems rely heavily on artificial intelligence capabilities to perform a variety of tasks. Sharing spectrum resources more efficiently, self organization, and interference mitigation are just a few examples. For many CR applications, a primary goal is to decentralize and distribute network functions among participant nodes. As a consequence, any given node in a CR network may be required to coordinate with not only its peers, but also with a number of unknown transmitters. Thus, it is desirable that individual nodes be capable of predicting future states of non-peer transmitters in order to better optimize their own operation. In this paper we introduce methods for identifying cognitive behavior in an unknown transmitter and predicting likely future states based on physical spectrum observations. We discuss the problem in the context of our Universal DSA Network Simulation (UDNS) and present two behavior classification algorithms used to this end.

Original languageEnglish (US)
Title of host publicationProceedings of the 2012 7th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications, CROWNCOM 2012
Pages280-284
Number of pages5
DOIs
StatePublished - Nov 26 2012
Externally publishedYes
Event2012 7th International ICST Conference on Cognitive Radio Oriented Wireless Ntworks and Communications, CROWNCOM 2012 - Stockholm, Sweden
Duration: Jun 18 2012Jun 20 2012

Publication series

NameProceedings of the 2012 7th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications, CROWNCOM 2012

Other

Other2012 7th International ICST Conference on Cognitive Radio Oriented Wireless Ntworks and Communications, CROWNCOM 2012
CountrySweden
CityStockholm
Period6/18/126/20/12

Keywords

  • AODE
  • Behavior Classification
  • Coginitive Radio
  • Dynamic Spectrum Access
  • Naive Bayes

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Communication

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  • Cite this

    DePoy, D., & Bose, T. (2012). Predictive behavior classification for cognitive radio: Introduction and preliminary results. In Proceedings of the 2012 7th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications, CROWNCOM 2012 (pp. 280-284). [6333754] (Proceedings of the 2012 7th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications, CROWNCOM 2012). https://doi.org/10.4108/icst.crowncom.2012.248518