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.
Cite
@article{arxiv.2504.13190,
title = {Cellular-X: An LLM-empowered Cellular Agent for Efficient Base Station Operations},
author = {Liujianfu Wang and Xinyi Long and Yuyang Du and Xiaoyan Liu and Kexin Chen and Soung Chang Liew},
journal= {arXiv preprint arXiv:2504.13190},
year = {2025}
}