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

Journal: Scientific reports
Published Date:

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.

Authors

  • Md Afzalur Rahman
    Space Science Centre, Institute of Climate Change , Universiti Kebangsaan Malaysia (UKM), Bangi, 43600, Malaysia.
  • Samir Salem Al-Bawri
    Space Science Centre, Institute of Climate Change , Universiti Kebangsaan Malaysia (UKM), Bangi, 43600, Malaysia. s.albawri@gmail.com.
  • Samia Larguech
    Department of Electrical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia. SRLarguech@pnu.edu.sa.
  • Sultan S Alharbi
    Department of Computer Science & Information Technology, Gulf Colleges, Hafar Al-Batin, Saudi Arabia.
  • Saeed Alsowail
    Information Technology Department, Tatweer Educational Technologies, Riyadh, 12264, Kingdom of Saudi Arabia.
  • Noorlindawaty Md Jizat
    Faculty of Artificial Intelligence and Engineering, Multimedia University, Cyberjaya, 62300, Malaysia. noorlindawaty.jizat@mmu.edu.my.
  • Mohammad Tariqul Islam
    Computer Science Department, Southern Connecticut State University, USA.

Keywords

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