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基于超材料的三频段紧凑型MIMO天线系统,用于具有机器学习性能验证的5G物联网应用。

Metamaterial based tri-band compact MIMO antenna system for 5G IoT applications with machine learning performance verification.

作者信息

Rahman Md Afzalur, Al-Bawri Samir Salem, Larguech Samia, Alharbi Sultan S, Alsowail Saeed, Jizat Noorlindawaty Md, Islam Mohammad Tariqul

机构信息

Space Science Centre, Institute of Climate Change , Universiti Kebangsaan Malaysia (UKM), Bangi, 43600, Malaysia.

Department of Electrical and Electronic Engineering, Daffodil International University, Dhaka, 1207, Bangladesh.

出版信息

Sci Rep. 2025 Jul 2;15(1):22866. doi: 10.1038/s41598-025-06391-1.

Abstract

This paper presents a novel tri-band Multiple Input Multiple Output (MIMO) antenna module designed for millimeter and microwave frequency bands, employing metamaterial (MTM) technology to enhance performance. The compact antenna module measures 36 × 36 × 1.6 mm and uses a Rogers RT-5880 substrate. Its structure includes a multi-stubbed radiating patch, a partial ground plane, and a 2 × 1 epsilon-negative MTM array positioned between antenna elements in an orthogonal layout. Operating at 3.5 GHz, 5.2 GHz, and 28 GHz, the integration of MTM significantly improves the antenna's overall performance by influencing phase, amplitude, and electromagnetic field distribution. Bandwidth enhancements of 10.01% and 6.4% are achieved for the 3.5 GHz and 5.2 GHz microwave bands, respectively, and 4.43% for the 28 GHz millimeter-wave band. Isolation levels improved from 20 dB to 24 dB in microwave bands and from 26 dB to 32 dB in the millimeter-wave band, ensuring reduced interference. The realized gain also increased from 3.6 dBi, 4.2 dBi, and 7.4 dBi to 4.8 dBi, 5.3 dBi, and 9.3 dBi across the respective frequency bands. The proposed MIMO antenna showcases excellent diversity performance with an envelope correlation coefficient (ECC) of below 0.002/0.001/0.0003 across all bands and a diversity gain (DG) exceeding 9.98 dB. Machine learning-based performance verification analysis assessed bandwidth and efficiency, where the K-Nearest Neighbors (KNN) model achieved 97.8% accuracy. This MIMO antenna holds great potential for various Internet of Things (IoT) applications, including Vehicle-to-Network, Vehicle-to-Cloud communications, 5G cellular networks, Wi-Fi, WiMAX, and both sub-6 GHz and millimeter-wave 5G bands, reinforcing its suitability for 5G IoT sectors.

摘要

本文介绍了一种新颖的三频段多输入多输出(MIMO)天线模块,该模块专为毫米波和微波频段设计,采用超材料(MTM)技术来提升性能。这款紧凑的天线模块尺寸为36×36×1.6毫米,使用罗杰斯RT - 5880基板。其结构包括一个多短截辐射贴片、一个部分接地平面以及一个以正交布局位于天线元件之间的2×1负介电常数MTM阵列。该天线在3.5吉赫兹、5.2吉赫兹和28吉赫兹频率下工作,MTM的集成通过影响相位、幅度和电磁场分布显著提高了天线的整体性能。在3.5吉赫兹和5.2吉赫兹微波频段,带宽分别提高了10.01%和6.4%,在28吉赫兹毫米波频段提高了4.43%。隔离度在微波频段从20分贝提高到24分贝,在毫米波频段从26分贝提高到32分贝,确保了干扰的降低。在各个频段,实现的增益也分别从3.6 dBi、4.2 dBi和7.4 dBi提高到4.8 dBi、5.3 dBi和9.3 dBi。所提出的MIMO天线在所有频段均展示出出色的分集性能,其包络相关系数(ECC)低于0.002/0.001/0.0003,分集增益(DG)超过9.98分贝。基于机器学习的性能验证分析评估了带宽和效率,其中K近邻(KNN)模型的准确率达到了97.8%。这款MIMO天线在包括车联网、车云通信、5G蜂窝网络、Wi-Fi、WiMAX以及低于6吉赫兹和毫米波5G频段在内的各种物联网(IoT)应用中具有巨大潜力,增强了其在5G物联网领域的适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e178/12218084/ce2cc9d25f92/41598_2025_6391_Fig1_HTML.jpg

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