用大模型自动设计天线，省去手动建模与调参
Large Language Model-Based Intelligent Antenna Design System
- 通过文本和图像生成天线模型，结合工程师交互迭代优化
- 将3.1-10.6GHz频段增益波动降低，保持原有增益水平
- 适合天线设计初学者或希望加速研发的工程师使用
天线仿真通常涉及建模与优化，过程耗时且人力密集，制约了天线分析与设计效率。本文提出一个基于大语言模型（LLM）的天线设计系统（LADS）原型，用于辅助天线仿真。LADS 能从学术论文、专利和技术报告中提取文本描述和图像，自动生成天线模型，并与工程师互动以迭代优化设计。随后，LADS 配置并运行优化器以满足设计规范。通过文献中的单极缝隙天线实例验证系统有效性：为提升3.1–10.6 GHz超宽带频段的增益稳定性，系统将十字缝隙改为H型缝隙并更换基板材料，经参数优化后，增益波动显著降低，同时维持原有增益水平。相关代码（LEAM）已开源：https://github.com/TaoWu974/LEAM。
原文摘要 · Abstract (English)
Antenna simulation typically involves modeling and optimization, which are time-consuming and labor-intensive, slowing down antenna analysis and design. This paper presents a prototype of a large language model (LLM)-based antenna design system (LADS) to assist in antenna simulation. LADS generates antenna models with textual descriptions and images extracted from academic papers, patents, and technical reports (either one or multiple), and it interacts with engineers to iteratively refine the designs. After that, LADS configures and runs an optimizer to meet the design specifications. The effectiveness of LADS is demonstrated by a monopole slotted antenna generated from images and descriptions from the literature. To improve gain stability across the 3.1-10.6 GHz ultra-wide band, LADS modifies the cross-slot into an H-slot and changes substrate material, followed by parameter optimization. As a result, the gain variation is reduced while maintaining the same gain level. The LLM-enabled antenna modeling (LEAM) is available at: https://github.com/TaoWu974/LEAM.
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