Decentralized and Dynamic Band Selection in Uplink Enhanced Licensed-Assisted Access: Deep Reinforcement Learning Approach
DC Field | Value | Language |
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dc.contributor.author | Tilahun, Fitsum Debebe | - |
dc.contributor.author | Kang, Chung G. | - |
dc.date.accessioned | 2021-08-31T05:58:59Z | - |
dc.date.available | 2021-08-31T05:58:59Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2020-03-27 | - |
dc.identifier.issn | 1530-8669 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/57213 | - |
dc.description.abstract | Enhanced licensed-assisted access (eLAA) is an operational mode that allows the use of unlicensed band to support long-term evolution (LTE) service via carrier aggregation technology. The extension of additional bandwidth is beneficial to meet the demands of the growing mobile traffic. In the uplink eLAA, which is prone to unexpected interference from WiFi access points, resource scheduling by the base station, and then performing a listen before talk (LBT) mechanism by the users can seriously affect the resource utilization. In this paper, we present a decentralized deep reinforcement learning (DRL)-based approach in which each user independently learns dynamic band selection strategy that maximizes its own rate. Through extensive simulations, we show that the proposed DRL-based band selection scheme improves resource utilization while supporting certain minimum quality of service (QoS). | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | WILEY-HINDAWI | - |
dc.title | Decentralized and Dynamic Band Selection in Uplink Enhanced Licensed-Assisted Access: Deep Reinforcement Learning Approach | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kang, Chung G. | - |
dc.identifier.doi | 10.1155/2020/5937358 | - |
dc.identifier.scopusid | 2-s2.0-85083205318 | - |
dc.identifier.wosid | 000525002200001 | - |
dc.identifier.bibliographicCitation | WIRELESS COMMUNICATIONS & MOBILE COMPUTING, v.2020 | - |
dc.relation.isPartOf | WIRELESS COMMUNICATIONS & MOBILE COMPUTING | - |
dc.citation.title | WIRELESS COMMUNICATIONS & MOBILE COMPUTING | - |
dc.citation.volume | 2020 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
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