Advanced LLM-Enhanced Intent-Based 5G Network Management using Dynamic Semantic Routes
As the use of Artificial Intelligence (AI) and Large Language Models (LLMs) is becoming common in everyday applications, their ability to interpret natural language has increased significantly. An emerging application of AI is integration with network management and orchestration practices. An instance of this integration is LLM-enhanced intent-based networking, where network operators will control a network using natural language. This work presents the use of dynamic routes with a semantic router to identify an intent from a network operator's prompt and extract necessary details for intent fulfillment in intent-based 5G+ core networks. Furthermore, the performance of static route selec...
| Authors | Thomas Benton Townsend, Dimitrios Michael Manias |
|---|---|
| Primary category | cs.NI |
| Published | 23 August 2026 |
| Last updated at source | 23 August 2026 |
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