Low-Complexity Learning for Dynamic Spectrum Access in Multi-User Multi-Channel Networks

Sunjung Kang, Changhee Joo

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

10 Citations (Scopus)


In Cognitive Radio Networks (CRNs), dynamic spectrum access allows (unlicensed) users to identify and access unused channels opportunistically, thus improves spectrum utility. In this paper, we address the user-channel allocation problem in multi-user multi-channel CRNs without a prior knowledge of channel statistics. A reward of a channel is stochastic with unknown distribution, and statistically different for each user. Each user either explores a channel to learn the channel statistics, or exploits the channel with the highest expected reward based on information collected so far. Further, a channel should be accessed exclusively by one user at a time due to a collision. Using multi-armed bandit framework, we develop a provably efficient solution whose computational complexity is linear to the number of users and channels.

Original languageEnglish
Title of host publicationINFOCOM 2018 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Electronic)9781538641286
Publication statusPublished - 2018 Oct 8
Externally publishedYes
Event2018 IEEE Conference on Computer Communications, INFOCOM 2018 - Honolulu, United States
Duration: 2018 Apr 152018 Apr 19

Publication series

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


Other2018 IEEE Conference on Computer Communications, INFOCOM 2018
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering


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