Two novel learning algorithms to solve the spectrum sharing problem in cognitive radio networks

Jing Zhang*, Dionysios I. Kountanis, Ala Al-Fuqaha

*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

To improve the spectral efficiency in cognitive radio networks, it is essential for cognitive radio users to be equipped with intelligent learning capability. Many different learning methods have been applied in different kinds of cognitive radio network models. This study presents two novel learning algorithms that can be applied to cognitive radio network models based on IEEE802.22. One is a no-regret learning method and the other is a reinforcement learning algorithm. The experimental results show that both methods can be effectively applied in cognitive radio networks. Moreover, the reinforcement learning out performs the no-regret learning method.

Original languageEnglish
Title of host publication2012 International Conference on Systems and Informatics, ICSAI 2012
Pages1472-1476
Number of pages5
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 International Conference on Systems and Informatics, ICSAI 2012 - Yantai, China
Duration: 19 May 201220 May 2012

Publication series

Name2012 International Conference on Systems and Informatics, ICSAI 2012

Conference

Conference2012 International Conference on Systems and Informatics, ICSAI 2012
Country/TerritoryChina
CityYantai
Period19/05/1220/05/12

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