Scholarlink

<p>This article presents an in-depth study on the optimization of a patch-type coupler specifically designed for 5G applications, leveraging a multi-objective binary genetic algorithm (MBGA) with multiple objectives. The optimization was conducted by exploiting an interface between MATLAB and CST, facilitating an effective synergy between modeling and analysis. The results of this optimization led to the development of a structure that resonates at 3.5&#xa0;GHz, offering exceptional performance tailored to the demands of 5G applications. Notably, the proposed coupler stands out with an impressive miniaturization rate of 70.76%, perfectly addressing contemporary needs for compactness and efficiency. The analysis of both simulated and measured results reveals a satisfactory agreement, thus demonstrating the robustness of the optimization method employed. This approach highlights not only the effectiveness of the binary genetic algorithm in the design of RF devices but also its potential to meet the growing challenges posed by 5G technology.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A multi-objective binary genetic algorithm for a low-profile, low-group delay directional coupler: an innovative design for 5G applications

  • 期刊论文

  • 发表日期：

    2025年7月1日

查看全文
  • Khadija Abouhssous,
  • Asmaa Zugari,
  • Moustapha El Bakkali,
  • Layla Wakrim,
  • Alia Zakriti

摘要

This article presents an in-depth study on the optimization of a patch-type coupler specifically designed for 5G applications, leveraging a multi-objective binary genetic algorithm (MBGA) with multiple objectives. The optimization was conducted by exploiting an interface between MATLAB and CST, facilitating an effective synergy between modeling and analysis. The results of this optimization led to the development of a structure that resonates at 3.5 GHz, offering exceptional performance tailored to the demands of 5G applications. Notably, the proposed coupler stands out with an impressive miniaturization rate of 70.76%, perfectly addressing contemporary needs for compactness and efficiency. The analysis of both simulated and measured results reveals a satisfactory agreement, thus demonstrating the robustness of the optimization method employed. This approach highlights not only the effectiveness of the binary genetic algorithm in the design of RF devices but also its potential to meet the growing challenges posed by 5G technology.