Approximation algorithms for wireless opportunistic spectrum scheduling in cognitive radio networks

Xiaohua Xu, Min Song

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

3 Scopus citations

Abstract

Given a set of communication links in cognitive radio networks, assume that the underlying channel state information along each link is unknown; however, we can estimate it by exploiting the feedbacks and evolutions of channel states. Assume time is divided into time-slots. Under the protocol interference model, the opportunistic spectrum scheduling problem aims to select interference-free links to transmit at each time-slot to maximize the average throughput over the long time horizon. Existing works on the opportunistic spectrum scheduling problem cannot satisfyingly address the wireless interference constraints. We apply the framework of restless multi-armed bandit and develop approximation algorithms for the problem with stochastic identical links and nonidentical links respectively. Based on the updated estimations of channel states, the proposed algorithms keep refining future link scheduling decisions. We also obtain approximation bounds of these two proposed algorithms.

Original languageEnglish
Title of host publicationIEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications
ISBN (Electronic)9781467399531
DOIs
StatePublished - 27 Jul 2016
Event35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016 - San Francisco, United States
Duration: 10 Apr 201614 Apr 2016

Publication series

NameProceedings - IEEE INFOCOM
Volume2016-July
ISSN (Print)0743-166X

Conference

Conference35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016
Country/TerritoryUnited States
CitySan Francisco
Period10/04/1614/04/16

Keywords

  • Approximation algorithm
  • Opportunistic spectrum scheduling
  • Protocol interference model
  • Restless multi-armed bandit

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