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

Khadija Abouhssous (), Asmaa Zugari, Moustapha El Bakkali, Layla Wakrim and Alia Zakriti
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Khadija Abouhssous: National School of Applied Sciences, Abdelmalek Essadi University
Asmaa Zugari: Abdelmalek Essadi University
Moustapha El Bakkali: Abdelmalek Essadi University
Layla Wakrim: Higher Institute of Engineering and Business (ISGA)
Alia Zakriti: National School of Applied Sciences, Abdelmalek Essadi University

Telecommunication Systems: Modelling, Analysis, Design and Management, 2025, vol. 88, issue 3, No 14, 13 pages

Abstract: Abstract 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.

Keywords: Multi-objective binary genetic algorithm; Patch coupler; Miniaturization; 5G applications (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11235-025-01328-5

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