LLM-Enabled NWDAF: A Step Toward AI-Native 6G Network Intelligence
Summary
This paper presents an open-source NWDAF compatible with Free5GC that integrates an LLM interface for natural language interaction and intent-based network management, aiming toward AI-native 6G networks.
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Paper page - LLM-Enabled NWDAF: A Step Toward AI-Native 6G Network Intelligence
Source: https://huggingface.co/papers/2606.11877
Abstract
An open-source Network Data Analytics Function compatible with Free5GC integrates a Large Language Model interface for natural language interaction and intent-based network management.
TheNetwork Data Analytics Function(NWDAF) is central to enabling zero-touch network management in fifth-generation (5G) networks by supporting real-time analytics and closed-loop automation. Despite its critical role, open-source NWDAF implementations remain limited in scope and accessibility. In this paper, we develop an open-source NWDAF, compatible with theopen-source core networkFree5GC, that collects network data via subscriptions toNetwork Functions(NFs), and also includes an integratedLarge Language Model(LLM) interface that enables natural language interaction with human operators. The interface processes user intents, encodes them using asemantic embedding model, and maps them to one of seven predefined intent categories to trigger analytics queries or event subscription commands. This architecture abstracts the complexity of traditional interfaces, allowing non-expert users to manage network analytics and subscriptions with ease. The system supports Access and Management Function (AMF) and Session Management Function (SMF) event subscriptions, real-time monitoring, and analytics retrieval viaPrometheus, all accessible through aconversational interface. By bridging AI-driven intent recognition with standardized network analytics, our implementation enhances operator usability and provides a foundation towards AI-native 6G networks. The source code and datasets generated during the current study are available in the github repository, https://github.com/HenokDanielbfg/testbed.
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