NETSOFT 2026, IEEE 12th International Conference on Network Softwarization, 29 June - 3 July 2026, Berlin, Germany
The 6G era introduces unprecedented complexity in managing heterogeneous, large-scale, and dynamic network infrastructures. These challenges are addressed by the concept of Intent-Based Networking (IBN), which has emerged as a promising paradigm for autonomous network management, enabling users to express high-level objectives that are automatically translated and enforced by the network. However, current IBN solutions remain constrained by rigid structured specifications and limited assurance mechanisms. This paper presents an overview of PhD research leveraging Generative AI (GenAI), specifically Large Language Models (LLMs), to address three fundamental IBN challenges: (i) intent translation, (ii) intent assurance, and (iii) GenAI operations in IBN systems. We propose a set of novel frameworks validated on real 5G/6G testbeds. Most contributions are supported by demos, datasets, and open-source implementations, which are referenced in the design section of each contribution. This PhD positions GenAI as a key enabler for advancing autonomous and user-centric 6G.
Type:
Conférence
City:
Berlin
Date:
2026-06-29
Department:
Systèmes de Communication
Eurecom Ref:
8875
Copyright:
© 2026 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
See also:
