Demo: Cellular-X: An LLM-empowered Cellular Agent for Efficient Base Station Operations
This paper introduces Cellular-X, an LLM-powered agent designed to automate cellular base station (BS) maintenance. Leveraging multimodal LLM and retrieval-augmented generation (RAG) techniques, Cellular-X significantly enhances field engineer efficiency by quickly interpreting user intents, retrieving relevant technical information, and configuring a BS through iterative self-correction. Key features of the demo include automatic customized BS setup, document-based query answering, and voice-controlled configuration reporting and revision. We implemented Cellular-X on a USRP X310 testbed for demonstration. Demo videos and implementation details are available at https://github.com/SeaBreezing/Cellular-X.
Authors
- L.L. Wang
- Soung Chang Liew (ORCID: https://orcid.org/0000-0001-7055-6483)
- Yuyang Du (ORCID: https://orcid.org/0000-0001-9213-9875)
- Kexin Chen (ORCID: https://orcid.org/0000-0001-5212-0635)
- Xingjian Long (ORCID: https://orcid.org/0009-0000-2789-9544)
- Xiaoyan Liu
Institutions
- Chinese University of Hong Kong (HK)
Publication Details
- Published
- 2025-06-23
- DOI
- https://doi.org/10.1145/3711875.3734372
- Primary Topic
- Vehicular Ad Hoc Networks (VANETs)
- Type
- article
- Field-Weighted Citation Impact
- 0.00