dc.citation.conferencePlace |
US |
- |
dc.citation.conferencePlace |
Honolulu |
- |
dc.citation.endPage |
1375 |
- |
dc.citation.startPage |
1367 |
- |
dc.citation.title |
IEEE International Conference on Computer Communications |
- |
dc.contributor.author |
Kang, Sunjung |
- |
dc.contributor.author |
Joo, Changhee |
- |
dc.date.accessioned |
2023-12-19T15:54:29Z |
- |
dc.date.available |
2023-12-19T15:54:29Z |
- |
dc.date.created |
2018-04-13 |
- |
dc.date.issued |
2018-04-15 |
- |
dc.description.abstract |
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 O(NK), where N denotes the number of users and K denotes the number of channels. |
- |
dc.identifier.bibliographicCitation |
IEEE International Conference on Computer Communications, pp.1367 - 1375 |
- |
dc.identifier.doi |
10.1109/INFOCOM.2018.8485937 |
- |
dc.identifier.issn |
0743-166X |
- |
dc.identifier.scopusid |
2-s2.0-85056191204 |
- |
dc.identifier.uri |
https://scholarworks.unist.ac.kr/handle/201301/32734 |
- |
dc.identifier.url |
https://ieeexplore.ieee.org/document/8485937 |
- |
dc.language |
영어 |
- |
dc.publisher |
IEEE |
- |
dc.title |
Low-complexity Learning for Dynamic Spectrum Access in Multi-User Multi-Channel Networks |
- |
dc.type |
Conference Paper |
- |
dc.date.conferenceDate |
2018-04-15 |
- |