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

Area of Science:

• Electrical Engineering
• Electromagnetics
• Antenna Theory

Background:

• Metamaterial (MTM) technology offers unique electromagnetic properties for antenna enhancement.
• Millimeter and microwave frequency bands are crucial for modern wireless communication, including 5G and IoT.
• Multiple Input Multiple Output (MIMO) antenna systems are essential for improving wireless link reliability and data rates.

Purpose of the Study:

• To design and present a compact, tri-band MIMO antenna module for millimeter and microwave frequencies.
• To investigate the performance enhancement achieved by integrating metamaterial structures.
• To validate the antenna's suitability for various high-frequency wireless applications, particularly 5G and IoT.

Main Methods:

• A novel tri-band MIMO antenna module was designed using a Rogers RT-5880 substrate with a compact 36x36x1.6 mm^3 footprint.
• A 2x1 epsilon-negative metamaterial array was orthogonally positioned between antenna elements to influence electromagnetic fields.
• Performance metrics including bandwidth, isolation, gain, envelope correlation coefficient (ECC), and diversity gain (DG) were evaluated.
• Machine learning, specifically the K-Nearest Neighbors (KNN) model, was employed for performance verification.

Main Results:

• The antenna operates effectively at 3.5 GHz, 5.2 GHz, and 28 GHz, covering both microwave and millimeter-wave bands.
• Significant improvements were observed: bandwidth increased by up to 10.01%, isolation improved to 24 dB (microwave) and 32 dB (millimeter-wave), and realized gain increased by up to 9.3 dBi.
• Excellent diversity performance was achieved with ECC below 0.002 and DG exceeding 9.98 dB.
• The KNN model achieved 97.8% accuracy in verifying antenna bandwidth and efficiency.

Conclusions:

• The proposed metamaterial-enhanced tri-band MIMO antenna demonstrates superior performance characteristics.
• Its compact size, wide operating frequencies, and excellent isolation make it ideal for 5G and IoT applications.
• The integration of metamaterials and machine learning-based verification offers a promising approach for advanced antenna design.