Q-learning for Opportunistic Spectrum Access

Omar Alsaleh*, Bechir Hamdaoui, Alan Fern

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

The expected shortage in spectrum supply is well understood to be primarily due to the inecient, static nature of current spectrum allocation policies. In order to address this problem, FCC promotes the so-called Opportunistic Spectrum Access (OSA). In short, the idea behind OSA is to allow un licensed users to use unused licensed spectra so long as they do not cause interference to licensed users. In this paper, we propose Q-OSA, a learning scheme that enables effective OSA, thus improving spectrum eciency. Q-OSA does not require prior knowledge of the environment's dynamics, yet can still achieve high performance by learning from interaction with the environment. Copywright

Original languageEnglish
Title of host publicationIWCMC 2010 - Proceedings of the 6th International Wireless Communications and Mobile Computing Conference
Pages220-224
Number of pages5
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event6th International Wireless Communications and Mobile Computing Conference, IWCMC 2010 - Caen, France
Duration: 28 Jun 20102 Jul 2010

Publication series

NameIWCMC 2010 - Proceedings of the 6th International Wireless Communications and Mobile Computing Conference

Conference

Conference6th International Wireless Communications and Mobile Computing Conference, IWCMC 2010
Country/TerritoryFrance
CityCaen
Period28/06/102/07/10

Keywords

  • Cognitive radio networks
  • Opportunistic/dynamic spectrum access
  • Q-learning

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