Enabling technologies for AI empowered 6G massive radio access networks
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shahjalal, M. | - |
dc.contributor.author | Kim, W. | - |
dc.contributor.author | Khalid, W. | - |
dc.contributor.author | Moon, S. | - |
dc.contributor.author | Khan, M. | - |
dc.contributor.author | Liu, S. | - |
dc.contributor.author | Lim, S. | - |
dc.contributor.author | Kim, E. | - |
dc.contributor.author | Yun, D.-W. | - |
dc.contributor.author | Lee, J. | - |
dc.contributor.author | Lee, W.-C. | - |
dc.contributor.author | Hwang, S.-H. | - |
dc.contributor.author | Kim, D. | - |
dc.contributor.author | Lee, J.-W. | - |
dc.contributor.author | Yu, H. | - |
dc.contributor.author | Sung, Y. | - |
dc.contributor.author | Jang, Y.M. | - |
dc.date.accessioned | 2023-09-12T01:40:05Z | - |
dc.date.available | 2023-09-12T01:40:05Z | - |
dc.date.issued | 2023-06 | - |
dc.identifier.issn | 2405-9595 | - |
dc.identifier.issn | 2405-9595 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/44268 | - |
dc.description.abstract | Predictably, the upcoming six generation (6G) networks demand ultra-massive interconnectivity comprising densely congested sustainable small-to-tiny networks. The conventional radio access network (RAN) will be redesigned to provide the necessary intelligence in all areas to meet required network flexibility, full coverage, and massive access. In this respect, this paper focuses on intelligent massive RAN (mRAN) architecture and key technologies fulfilling the requirements. Particularly, we investigate potential AI algorithms for network and resource management issues in 6G mRAN. Furthermore, we summarize the research issues in edge technologies and physical layer intelligence on 6G network architecture. © 2022 The Author(s) | - |
dc.format.extent | 15 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Korean Institute of Communication Sciences | - |
dc.title | Enabling technologies for AI empowered 6G massive radio access networks | - |
dc.title.alternative | Enabling technologies for AI empowered 6G massive radio access networks | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.icte.2022.07.002 | - |
dc.identifier.bibliographicCitation | ICT Express, v.9, no.3, pp 341 - 355 | - |
dc.identifier.kciid | ART002977344 | - |
dc.identifier.wosid | 001025312000001 | - |
dc.identifier.scopusid | 2-s2.0-85135172179 | - |
dc.citation.endPage | 355 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 341 | - |
dc.citation.title | ICT Express | - |
dc.citation.volume | 9 | - |
dc.identifier.url | https://linkinghub.elsevier.com/retrieve/pii/S2405959522000996 | - |
dc.publisher.location | 대한민국 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | Y | - |
dc.subject.keywordAuthor | 6G | - |
dc.subject.keywordAuthor | AI-assisted networking | - |
dc.subject.keywordAuthor | Edge AI | - |
dc.subject.keywordAuthor | Massive radio access networks | - |
dc.subject.keywordPlus | INTELLIGENT REFLECTING SURFACE | - |
dc.subject.keywordPlus | LEARNING-BASED APPROACH | - |
dc.subject.keywordPlus | RESOURCE-MANAGEMENT | - |
dc.subject.keywordPlus | TRAFFIC PREDICTION | - |
dc.subject.keywordPlus | CELLULAR NETWORKS | - |
dc.subject.keywordPlus | POWER ALLOCATION | - |
dc.subject.keywordPlus | MIMO SYSTEMS | - |
dc.subject.keywordPlus | DEEP | - |
dc.subject.keywordPlus | COMMUNICATION | - |
dc.subject.keywordPlus | CHALLENGES | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
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