A Survey of Integrating Generative Artificial Intelligence and 6G Mobile Services: Architectures, Solutions, Technologies and Outlooks
Generative artificial intelligence (GenAI) is rapidly driving a new phase of artificial intelligence revolution, marked by various applications such as ChatGPT, Sora and DeepSeek. With powerful capabilities in content generation, personalization and user interaction, GenAI can drive significant enhancements in various mobile services to satisfy individual user preferences. Meanwhile, mobile services offer substantial support for accessibility, functionality and intelligence of GenAI applications. However, current research on integrating GenAI and mobile services remains nascent, lacking necessary theoretical and technical support. In this survey, we break down a new vision to guide research on integrating GenAI and mobile services, aiming to improve 6G intelligence levels and enable 6G mobile networks to support the integration of GenAI and mobile services effectively. We begin by examining the necessity of integrating GenAI with 6G mobile services and exploring potential learning architectures of GenAI models within mobile networks. Next, we analyze potential solutions from two perspectives: how 6G mobile networks empower GenAI and how GenAI enables mobile services. We subsequently explore a promising use case, along with essential features and techniques, to facilitate the integration of GenAI and mobile services. Finally, we discuss future research directions, aiming at realizing intelligent 6G networks.
Authors
- Bin Cao (ORCID: https://orcid.org/0000-0001-8839-243X)
- Dong In Kim (ORCID: https://orcid.org/0000-0001-7711-8072)
- Xinyi Xu (ORCID: https://orcid.org/0000-0001-6916-5629)
- Rahim Tafazolli (ORCID: https://orcid.org/0000-0002-6062-8639)
- Yi-Jing Liu (ORCID: https://orcid.org/0009-0006-3019-5795)
- Ruichen Zhang (ORCID: https://orcid.org/0000-0002-6859-3645)
- Hongyang Du (ORCID: https://orcid.org/0000-0002-8220-6525)
- Khaled B. Letaief (ORCID: https://orcid.org/0000-0003-2519-6401)
- Abbas Jamalipour (ORCID: https://orcid.org/0000-0002-1807-7220)
- Gang Feng (ORCID: https://orcid.org/0000-0002-2512-2392)
- Dusit Niyato (ORCID: https://orcid.org/0000-0002-7442-7416)
Institutions
- The University of Sydney (AU)
- Beijing University of Posts and Telecommunications (CN)
- University of Electronic Science and Technology of China (CN)
- Nanyang Technological University (SG)
- Hong Kong University of Science and Technology (HK)
- University of Surrey (GB)
- Sungkyunkwan University (KR)
- University of Hong Kong (HK)
Publication Details
- Journal
- IEEE Transactions on Cognitive Communications and Networking
- Published
- 2025-04-08
- DOI
- https://doi.org/10.1109/tccn.2025.3558992
- Citations
- 14
- Primary Topic
- IoT and Edge/Fog Computing
- Type
- article
- Field-Weighted Citation Impact
- 20.82