Machine Learning-Based Printed Lens Antenna With Graded-Index Metasurface for mmWave 5G NR N261 Mobile Communication Applications

IF 1.8 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Communication Systems Pub Date : 2025-07-07 DOI:10.1002/dac.70176

K. Vasu Babu, Gorre Naga Jyothi Sree, Sudipta Das, Wael Ali, Torki Altameem, Walid El-Shafai

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Abstract

This article presents an advanced metasurface-based printed antenna, leveraging a machine learning (ML) optimization method for millimeter-wave 5G New Radio (NR) communication networks. The ML-based Random Forest, Artificial Neural Networks (ANN), and XG Boost algorithms are developed and implemented to optimize the antenna performance parameters. The improvement of gain is discussed through the implementation of a phase-oriented graded-index meta-lens system for the designed 28-GHz 5G rectangular microstrip patch design (RMPD). The intended metamaterial (MTM) unit cells are designed and placed on the graded metasurface lens with a radial phase to analyze transmission characteristics. The designed meta-lens antenna offers gain enhancement by 2.32 dBi due to the meta-lens focusing effect in the intended direction. The designed patch antenna integrated with the lens exhibits a peak gain of around 8.33 dBi and efficiency above 98% within an operating band (27.5–29.1 GHz). The suggested metasurface antenna supports the 5G New Radio (5G NR) n261 (27.5–28.35 GHz) FR-2 band. The performance parameters of the simple patch antenna and metasurface Luneburg lens-integrated antenna structures have been evaluated and analyzed theoretically, followed by experimental validation of the fabricated prototypes. The finite element method-based full-wave simulation outcomes are validated with measurement results, which justify the correctness of the prescribed design approach to achieve improved gain for mm-wave 5G patch antenna.

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用于毫米波5G NR N261移动通信应用的基于机器学习的梯度指数超表面印刷透镜天线

本文介绍了一种先进的基于超表面的印刷天线，利用机器学习（ML）优化方法用于毫米波5G新无线电（NR）通信网络。开发并实现了基于ml的随机森林、人工神经网络（ANN）和XG Boost算法来优化天线性能参数。通过在设计的28 ghz 5G矩形微带贴片设计（RMPD）中实现面向相位的渐变折射率元透镜系统，讨论了增益的提高。设计了预期的超材料（MTM）单元电池，并将其放置在具有径向相位的梯度超表面透镜上，以分析其传输特性。由于元透镜在预期方向上的聚焦效应，所设计的元透镜天线的增益增强了2.32 dBi。与透镜集成的贴片天线在工作频段（27.5-29.1 GHz）内的峰值增益约为8.33 dBi，效率高于98%。建议的超表面天线支持5G NR (5G New Radio) n261 (27.5-28.35 GHz) FR-2频段。对简单贴片天线和超表面吕讷堡透镜集成天线结构的性能参数进行了理论评价和分析，并对制作的样机进行了实验验证。基于有限元法的全波仿真结果与实测结果进行了验证，验证了所设计方法的正确性，从而提高了毫米波5G贴片天线的增益。

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来源期刊

International Journal of Communication Systems 工程技术-电信学

CiteScore

5.90

自引率

9.50%

发文量

323

审稿时长

7.9 months

期刊介绍： The International Journal of Communication Systems provides a forum for R&D, open to researchers from all types of institutions and organisations worldwide, aimed at the increasingly important area of communication technology. The Journal''s emphasis is particularly on the issues impacting behaviour at the system, service and management levels. Published twelve times a year, it provides coverage of advances that have a significant potential to impact the immense technical and commercial opportunities in the communications sector. The International Journal of Communication Systems strives to select a balance of contributions that promotes technical innovation allied to practical relevance across the range of system types and issues. The Journal addresses both public communication systems (Telecommunication, mobile, Internet, and Cable TV) and private systems (Intranets, enterprise networks, LANs, MANs, WANs). The following key areas and issues are regularly covered: -Transmission/Switching/Distribution technologies (ATM, SDH, TCP/IP, routers, DSL, cable modems, VoD, VoIP, WDM, etc.) -System control, network/service management -Network and Internet protocols and standards -Client-server, distributed and Web-based communication systems -Broadband and multimedia systems and applications, with a focus on increased service variety and interactivity -Trials of advanced systems and services; their implementation and evaluation -Novel concepts and improvements in technique; their theoretical basis and performance analysis using measurement/testing, modelling and simulation -Performance evaluation issues and methods.