Windmann, StefanStefanWindmannAlbrecht, JanisJanisAlbrechtFriesen, MaximMaximFriesenJasperneite, JürgenJürgenJasperneite2025-10-272025-10-272025https://publica.fraunhofer.de/handle/publica/49773310.1109/ETFA65518.2025.11205555In this paper, the use of Large Language Models (LLMs) for the configuration of hybrid TSN/5G networks is investigated. We discuss promising use cases where LLMs offer significant potential to simplify complex configuration tasks. Particularly, we consider two important scenarios: In the first scenario, the LLM functions as an engineering component enhancing traditional network control entities such as the Centralized User Configurations (CUCs) and Centralized Network Configurations (CNCs) of TSN networks and interacting with the 5G control plane. In the second scenario, the LLM serves as an interactive assistance tool for users performing manual configuration tasks. For these use cases, an LLM-based architecture for network configuration is proposed, which consists of a Retrieval-Augmented Generation (RAG) system, a verification component, and an orchestration layer. Within the framework of this architecture, we introduce LLM-based methods to enhance the reliability of configuration in complex real-time networks, leveraging strategies such as divide and conquer, prompt engineering, and verification.en5G mobile communicationLarge language modelsRetrieval augmented generationManualsEthernetReliability engineeringReal-time systemsPrompt engineeringManufacturing automationLarge Language Model (LLM)Time Sensitive Networking (TSN)5GNetwork EngineeringNETCONFYANGconference paper