WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks

• URL: http://arxiv.org/abs/2409.07964v1
• Date: Thu, 12 Sep 2024 11:48:01 GMT
• Title: WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks
• Authors: Jingwen Tong, Jiawei Shao, Qiong Wu, Wei Guo, Zijian Li, Zehong Lin, Jun Zhang,
• Abstract summary: Wireless networks are increasingly facing challenges due to their expanding scale and complexity. These challenges underscore the need for advanced AI-driven strategies, particularly in the upcoming 6G networks. We introduce WirelessAgent, a novel approach to develop AI agents capable of managing complex tasks in wireless networks.
• Score: 16.722524706176767
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Wireless networks are increasingly facing challenges due to their expanding scale and complexity. These challenges underscore the need for advanced AI-driven strategies, particularly in the upcoming 6G networks. In this article, we introduce WirelessAgent, a novel approach leveraging large language models (LLMs) to develop AI agents capable of managing complex tasks in wireless networks. It can effectively improve network performance through advanced reasoning, multimodal data processing, and autonomous decision making. Thereafter, we demonstrate the practical applicability and benefits of WirelessAgent for network slicing management. The experimental results show that WirelessAgent is capable of accurately understanding user intent, effectively allocating slice resources, and consistently maintaining optimal performance.

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