Centralized Spectrum Sharing Using Reinforcement Learning

Yang Miao, Ye Neng, Li Jianguo, Yu Hanxiao

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

Abstract

Spectrum sharing technologies are a kind of important technologies to overcome the shortage of the wireless spectrum, among which the centralized spectrum sharing exhibits superior performance in dense region. However, this method does suffer from large computational complexity and impractical implementation when optimization target is and overall system is complex. In this paper, reinforcement learning based centralized spectrum sharing is studied. Simulations results show that the proposed method holds good performance.

Original languageEnglish
Title of host publicationProceedings - 2016 3rd International Conference on Information Science and Control Engineering, ICISCE 2016
EditorsShaozi Li, Yun Cheng, Ying Dai
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1275-1280
Number of pages6
ISBN (Electronic)9781509025350
DOIs
Publication statusPublished - 31 Oct 2016
Event3rd International Conference on Information Science and Control Engineering, ICISCE 2016 - Beijing, China
Duration: 8 Jul 201610 Jul 2016

Publication series

NameProceedings - 2016 3rd International Conference on Information Science and Control Engineering, ICISCE 2016

Conference

Conference3rd International Conference on Information Science and Control Engineering, ICISCE 2016
Country/TerritoryChina
CityBeijing
Period8/07/1610/07/16

Keywords

  • Centralized
  • LTE-U
  • Reinforcement learning
  • Spectrum sharing

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