AI-RAN in 6G Networks: State-of-the-Art and Challenges
6G is a next-generation cellular communication technology that builds up on existing 5G networks which are currently rolled out worldwide. Through incorporation of artificial intelligence (AI) and machine learning (ML), the core 5G network is advanced into an intelligent 6G network. The 6G Artificia...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of the Communications Society |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10360202/ |
| _version_ | 1797365935678423040 |
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| author | Naveed Ali Khan Stefan Schmid |
| author_facet | Naveed Ali Khan Stefan Schmid |
| author_sort | Naveed Ali Khan |
| collection | DOAJ |
| description | 6G is a next-generation cellular communication technology that builds up on existing 5G networks which are currently rolled out worldwide. Through incorporation of artificial intelligence (AI) and machine learning (ML), the core 5G network is advanced into an intelligent 6G network. The 6G Artificial Intelligence Radio Access Network (AI-RAN) is anticipated to offer advanced features like reduced latency, improved bandwidth, data rates and coverage. Furthermore, AI-RAN is expected to support complex use cases such as extreme connectivity, multi-user communications and dynamic spectrum access. This paper provides a detailed survey and thorough assessment of AI-RAN’s vision and state-of-the-art challenges. We first present a concise introduction to 6G AI-RAN followed by background information on the current 5G RAN and its challenges that must be overcome to implement 6G AI-RAN. The paper then examines trending research issues in AI-RAN, i.e., challenges related to spectrum allocation, network architecture, and resource management. We discuss the methods to overcome these challenges which include the adoption of advanced machine learning and edge computing technologies to boost the performance of 6G AI-RAN. We conclude by stating open research directions. |
| first_indexed | 2024-03-08T16:57:04Z |
| format | Article |
| id | doaj.art-a1f0df48564f475d99a31cb52ee3333e |
| institution | Directory Open Access Journal |
| issn | 2644-125X |
| language | English |
| last_indexed | 2024-03-08T16:57:04Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of the Communications Society |
| spelling | doaj.art-a1f0df48564f475d99a31cb52ee3333e2024-01-05T00:04:57ZengIEEEIEEE Open Journal of the Communications Society2644-125X2024-01-01529431110.1109/OJCOMS.2023.334306910360202AI-RAN in 6G Networks: State-of-the-Art and ChallengesNaveed Ali Khan0https://orcid.org/0000-0002-1084-590XStefan Schmid1https://orcid.org/0000-0002-7798-1711Department of Internet Architecture and Management, Technical University Berlin, Berlin, GermanyDepartment of Internet Architecture and Management, Technical University Berlin, Berlin, Germany6G is a next-generation cellular communication technology that builds up on existing 5G networks which are currently rolled out worldwide. Through incorporation of artificial intelligence (AI) and machine learning (ML), the core 5G network is advanced into an intelligent 6G network. The 6G Artificial Intelligence Radio Access Network (AI-RAN) is anticipated to offer advanced features like reduced latency, improved bandwidth, data rates and coverage. Furthermore, AI-RAN is expected to support complex use cases such as extreme connectivity, multi-user communications and dynamic spectrum access. This paper provides a detailed survey and thorough assessment of AI-RAN’s vision and state-of-the-art challenges. We first present a concise introduction to 6G AI-RAN followed by background information on the current 5G RAN and its challenges that must be overcome to implement 6G AI-RAN. The paper then examines trending research issues in AI-RAN, i.e., challenges related to spectrum allocation, network architecture, and resource management. We discuss the methods to overcome these challenges which include the adoption of advanced machine learning and edge computing technologies to boost the performance of 6G AI-RAN. We conclude by stating open research directions.https://ieeexplore.ieee.org/document/10360202/5G6GAI-RANAI/MLradio and future Internet architecture |
| spellingShingle | Naveed Ali Khan Stefan Schmid AI-RAN in 6G Networks: State-of-the-Art and Challenges IEEE Open Journal of the Communications Society 5G 6G AI-RAN AI/ML radio and future Internet architecture |
| title | AI-RAN in 6G Networks: State-of-the-Art and Challenges |
| title_full | AI-RAN in 6G Networks: State-of-the-Art and Challenges |
| title_fullStr | AI-RAN in 6G Networks: State-of-the-Art and Challenges |
| title_full_unstemmed | AI-RAN in 6G Networks: State-of-the-Art and Challenges |
| title_short | AI-RAN in 6G Networks: State-of-the-Art and Challenges |
| title_sort | ai ran in 6g networks state of the art and challenges |
| topic | 5G 6G AI-RAN AI/ML radio and future Internet architecture |
| url | https://ieeexplore.ieee.org/document/10360202/ |
| work_keys_str_mv | AT naveedalikhan airanin6gnetworksstateoftheartandchallenges AT stefanschmid airanin6gnetworksstateoftheartandchallenges |