Bridging Large Language Models and 6G Networks: Overview and Open Issues

Large language models (LLMs) are rapidly transforming the design and operation of communication systems, while the advent of sixth-generation (6G) networks provides the infrastructure necessary to sustain their unprecedented scale. This survey investigates the bidirectional relationship between LLMs and 6G networks from two complementary perspectives. From the perspective of LLM for Network, we illustrate how LLMs can enhance network management, strengthen security, optimize resource allocation, and act as intelligent agents. By leveraging their natural language understanding and reasoning capabilities, LLMs offer new opportunities for intent-driven orchestration, anomaly detection, and adaptive optimization beyond the scope of conventional AI models. From the perspective of Network for LLM, we discuss how 6G-native features such as integrated sensing and communication, semantic-aware transmission, and green resource management enable scalable, efficient, and sustainable training and inference of LLMs at the edge and in the cloud. Building on these two perspectives, we identify key challenges related to scalability and efficiency, robustness and security, as well as trustworthiness and sustainability. We further highlight open research directions as well. We envision that this work serves as a roadmap for cross-disciplinary research, fostering the integration of LLMs and 6G toward trustworthy and intelligent next-generation communication systems.