Leveraging LLM-Powered Intelligent Chatbots for Intent-Based Networking in 5G Modem Reconfiguration

Intent-Based Networking (IBN) has simplified network management and orchestration at a high level, but configuring User Equipment (UE), like 5G modems, is still a complex and demanding task due to dynamic requirements and intricate device-specific settings, and scalability challenges, especially when dealing with distributed, edge-based devices. This paper explores the potential of using Intelligent Chatbots powered by Generative Artificial Intelligence and Large Language Models (LLMs) operating as co-pilots to automate and optimize modem configurations. We propose a scalable chatbot system that translates user intents into actionable configurations, enhancing security, performance, and adaptability. To this end, we introduce a middleware that bridges LLMs with 5G Modem interfaces, eliminating retraining needs while ensuring engaging, real-time interaction with users. Additionally, we analyze key challenges in integrating LLM-based chatbots with UE and discuss the benefits of query caching in optimizing response times. Our findings highlight the potential of Intelligent Chatbots in extending IBN principles to UE, enabling a more automated and user-friendly approach to network configuration.