Large Language Model-Based Intelligent Antenna Design System
This paper presents a prototype of a large language model (LLM)-based antenna design system (LADS) that generates antenna models from textual descriptions and images, and interacts with engineers to refine the designs before optimizing the parameters.
Why it matters
This LLM-based antenna design system has the potential to significantly accelerate the antenna analysis and optimization process, which is crucial for the development of advanced wireless communication systems.
Key Points
- 1LADS generates antenna models from textual descriptions and images in academic papers, patents, and technical reports
- 2LADS interacts with engineers to iteratively refine the antenna designs
- 3LADS configures and runs an optimizer to meet the design specifications
- 4The effectiveness of LADS is demonstrated by optimizing a monopole slotted antenna for improved gain stability across the ultra-wide band
Details
The paper introduces a novel LLM-based antenna design system (LADS) that aims to streamline the typically time-consuming and labor-intensive process of antenna simulation and optimization. LADS can generate antenna models from textual descriptions and images extracted from various technical sources, and then work with engineers to iteratively refine the designs. After that, LADS configures and runs an optimizer to meet the specified design requirements. The authors demonstrate the effectiveness of LADS by using it to optimize a monopole slotted antenna for improved gain stability across the 3.1-10.6 GHz ultra-wide band. LADS was able to modify the antenna's cross-slot into an H-slot and change the substrate material, leading to reduced gain variation while maintaining the same gain level.
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