Evolving Towards Artificial-Intelligence-Driven Sixth-Generation Mobile Networks: An End-to-End Framework, Key Technologies, and Opportunities

The incorporation of artificial intelligence (AI) into sixth-generation (6G) mobile networks is expected to revolutionize communication systems, transforming them into intelligent platforms that provide seamless connectivity and intelligent services. This paper explores the evolution of 6G architect...

Full description

Saved in:
Bibliographic Details
Main Authors: Zexu Li, Jingyi Wang, Song Zhao, Qingtian Wang, Yue Wang
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/15/6/2920
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850205845585920000
author Zexu Li
Jingyi Wang
Song Zhao
Qingtian Wang
Yue Wang
author_facet Zexu Li
Jingyi Wang
Song Zhao
Qingtian Wang
Yue Wang
author_sort Zexu Li
collection DOAJ
description The incorporation of artificial intelligence (AI) into sixth-generation (6G) mobile networks is expected to revolutionize communication systems, transforming them into intelligent platforms that provide seamless connectivity and intelligent services. This paper explores the evolution of 6G architectures, as well as the enabling technologies required to integrate AI across the cloud, core network (CN), radio access network (RAN), and terminals. It begins by examining the necessity of embedding AI into 6G networks, making it a native capability. The analysis then outlines potential evolutionary paths for the RAN architecture and proposes an end-to-end AI-driven framework. Additionally, key technologies such as cross-domain AI collaboration, native computing, and native security mechanisms are discussed. The study identifies potential use cases, including embodied intelligence, wearable devices, and generative AI, which offer valuable insights into fostering collaboration within the AI-driven ecosystem and highlight new revenue model opportunities and challenges. The paper concludes with a forward-looking perspective on the convergence of AI and 6G technology.
format Article
id doaj-art-c40765115fa24c05b7f69b0cefcde416
institution OA Journals
issn 2076-3417
language English
publishDate 2025-03-01
publisher MDPI AG
record_format Article
series Applied Sciences
spelling doaj-art-c40765115fa24c05b7f69b0cefcde4162025-08-20T02:11:00ZengMDPI AGApplied Sciences2076-34172025-03-01156292010.3390/app15062920Evolving Towards Artificial-Intelligence-Driven Sixth-Generation Mobile Networks: An End-to-End Framework, Key Technologies, and OpportunitiesZexu Li0Jingyi Wang1Song Zhao2Qingtian Wang3Yue Wang4China Telecom Research Institute, Beiqijia Town, Beijing 102209, ChinaChina Telecom Research Institute, Beiqijia Town, Beijing 102209, ChinaChina Telecom Research Institute, Beiqijia Town, Beijing 102209, ChinaChina Telecom Research Institute, Beiqijia Town, Beijing 102209, ChinaChina Telecom Research Institute, Beiqijia Town, Beijing 102209, ChinaThe incorporation of artificial intelligence (AI) into sixth-generation (6G) mobile networks is expected to revolutionize communication systems, transforming them into intelligent platforms that provide seamless connectivity and intelligent services. This paper explores the evolution of 6G architectures, as well as the enabling technologies required to integrate AI across the cloud, core network (CN), radio access network (RAN), and terminals. It begins by examining the necessity of embedding AI into 6G networks, making it a native capability. The analysis then outlines potential evolutionary paths for the RAN architecture and proposes an end-to-end AI-driven framework. Additionally, key technologies such as cross-domain AI collaboration, native computing, and native security mechanisms are discussed. The study identifies potential use cases, including embodied intelligence, wearable devices, and generative AI, which offer valuable insights into fostering collaboration within the AI-driven ecosystem and highlight new revenue model opportunities and challenges. The paper concludes with a forward-looking perspective on the convergence of AI and 6G technology.https://www.mdpi.com/2076-3417/15/6/29206GAI-native RANend-to-end AIcross-domain
spellingShingle Zexu Li
Jingyi Wang
Song Zhao
Qingtian Wang
Yue Wang
Evolving Towards Artificial-Intelligence-Driven Sixth-Generation Mobile Networks: An End-to-End Framework, Key Technologies, and Opportunities
Applied Sciences
6G
AI-native RAN
end-to-end AI
cross-domain
title Evolving Towards Artificial-Intelligence-Driven Sixth-Generation Mobile Networks: An End-to-End Framework, Key Technologies, and Opportunities
title_full Evolving Towards Artificial-Intelligence-Driven Sixth-Generation Mobile Networks: An End-to-End Framework, Key Technologies, and Opportunities
title_fullStr Evolving Towards Artificial-Intelligence-Driven Sixth-Generation Mobile Networks: An End-to-End Framework, Key Technologies, and Opportunities
title_full_unstemmed Evolving Towards Artificial-Intelligence-Driven Sixth-Generation Mobile Networks: An End-to-End Framework, Key Technologies, and Opportunities
title_short Evolving Towards Artificial-Intelligence-Driven Sixth-Generation Mobile Networks: An End-to-End Framework, Key Technologies, and Opportunities
title_sort evolving towards artificial intelligence driven sixth generation mobile networks an end to end framework key technologies and opportunities
topic 6G
AI-native RAN
end-to-end AI
cross-domain
url https://www.mdpi.com/2076-3417/15/6/2920
work_keys_str_mv AT zexuli evolvingtowardsartificialintelligencedrivensixthgenerationmobilenetworksanendtoendframeworkkeytechnologiesandopportunities
AT jingyiwang evolvingtowardsartificialintelligencedrivensixthgenerationmobilenetworksanendtoendframeworkkeytechnologiesandopportunities
AT songzhao evolvingtowardsartificialintelligencedrivensixthgenerationmobilenetworksanendtoendframeworkkeytechnologiesandopportunities
AT qingtianwang evolvingtowardsartificialintelligencedrivensixthgenerationmobilenetworksanendtoendframeworkkeytechnologiesandopportunities
AT yuewang evolvingtowardsartificialintelligencedrivensixthgenerationmobilenetworksanendtoendframeworkkeytechnologiesandopportunities