Zhaoyang Li, Xingzhi Jin, Junyu Pan, Qianqian Yang, Zhiguo Shi
This paper explores the use of large language models for creating intent-aware, autonomous agents to manage the complexity of 6G wireless communication systems.
As we move towards 6G wireless systems, the complexity of communication networks and the variety of user needs are increasing. Traditional rule-based systems are no longer sufficient, and there is a shift towards using intelligent systems that can understand user intent and adapt accordingly. This paper discusses how large language models (LLMs), which can understand context and reason across different types of information, can help create network agents that make autonomous decisions based on user needs. The authors also present a case study of a system that uses these principles to manage communication links based on user preferences and changing conditions.
