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arXiv · 2512.18582

Wireless Copilot: An AI-Powered Partner for Navigating Next-Generation Wireless Complexity

Haoxiang Luo·Ruichen Zhang·Yinqiu Liu·Gang Sun·Hongfang Yu·Dong In Kim
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Abstract

The sixth-generation (6G) of wireless networks introduces a level of operational complexity that exceeds the limits of traditional automation and manual oversight. This paper introduces the "Wireless Copilot," an AI-powered technical assistant designed to function as a collaborative partner for human network designers, engineers, and operators. We posit that by integrating Large Language Models (LLMs) with a robust cognitive framework. It will interact with wireless devices, transmitting the user's intentions into the actual network execution process. Then, Wireless Copilot can translate high-level human intent into precise, optimized, and verifiable network actions. This framework bridges the gap between human expertise and machine-scale complexity, enabling more efficient, intelligent, and trustworthy management of 6G systems. Wireless Copilot will be a novel layer between the wireless infrastructure and the network operators. Moreover, we explore \emph{Wireless Copilot}'s methodology and analyze its application in Low-Altitude Wireless Networks (LAWNets) assisting 6G, including network design, configuration, evaluation, and optimization. Additionally, we present a case study on intent-based LAWNets resource allocation, demonstrating its superior adaptability compared to others. Finally, we outline future directions toward creating a comprehensive human-AI collaborative ecosystem for the 6G.

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Haoxiang Luo, Ruichen Zhang, Yinqiu Liu, Gang Sun, Hongfang Yu, Dong In Kim. 2025-12-21. Wireless Copilot: An AI-Powered Partner for Navigating Next-Generation Wireless Complexity. https://arxiv.org/abs/2512.18582

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