TY - JOUR
T1 - A Survey of Integrating Generative Artificial Intelligence and 6G Mobile Services
T2 - Architectures, Solutions, Technologies and Outlooks
AU - Liu, Yi Jing
AU - Du, Hongyang
AU - Xu, Xinyi
AU - Zhang, Ruichen
AU - Feng, Gang
AU - Cao, Bin
AU - Niyato, Dusit
AU - Kim, Dong In
AU - Jamalipour, Abbas
AU - Letaief, Khaled B.
AU - Tafazolli, Rahim
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - Generative artificial intelligence
KW - mobile networks
KW - mobile services
KW - network intelligence
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001510078900050
UR - https://openalex.org/W4409249316
UR - https://www.scopus.com/pages/publications/105002454845
U2 - 10.1109/TCCN.2025.3558992
DO - 10.1109/TCCN.2025.3558992
M3 - Journal Article
SN - 2332-7731
VL - 11
SP - 1334
EP - 1356
JO - IEEE Transactions on Cognitive Communications and Networking
JF - IEEE Transactions on Cognitive Communications and Networking
IS - 3
ER -