Enabling technologies for AI empowered 6G massive radio access networksopen access
- Authors
- Md. Shahjalal; Kim, Woojun; Khalid, Waqas; Moon, Seokjae; Khan, Murad; Liu, ShuZhi; Lim, Suhyeon; Kim, Eunjin; Yun, Deok-Won; Lee, Joohyun; Lee, Won-Cheol; Hwang, Seung-Hoon; Kim, Dongkyun; Lee, Jang-Won; Yu, Heejung; Sung, Youngchul; Jang, Yeong Min
- Issue Date
- Jun-2023
- Publisher
- 한국통신학회
- Keywords
- 6G; AI-assisted networking; Edge AI; Massive radio access networks
- Citation
- ICT Express, v.9, no.3, pp 341 - 355
- Pages
- 15
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- ICT Express
- Volume
- 9
- Number
- 3
- Start Page
- 341
- End Page
- 355
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/3821
- DOI
- 10.1016/j.icte.2022.07.002
- ISSN
- 2405-9595
2405-9595
- 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)
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Collections - College of Engineering > Department of Electronics and Electrical Engineering > 1. Journal Articles

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