volume | PIER Journals

Abstract

This article presents a compact and flexible ultra-wideband (UWB) antenna with a defected ground structure (DGS) for IoT applications. The antenna is fabricated on a 0.7 mm thick jeans substrate to ensure high flexibility and take advantage of its universal availability. Machine learning techniques are applied to optimize the antenna's performance. A ring-shaped patch with DGS and C-type stubs is used to achieve a large bandwidth and reduce size. The total dimension of the proposed flexible antenna is 38 × 26 × 1.7 mm³. The primary aim of this article is to design a flexible UWB antenna with a remarkable impedance bandwidth of 131.45%, which covers frequencies from 2.56 GHz to 12.38 GHz. It operates at 3, 8, and 11.32 GHz frequencies with 99%, 98.30%, and 96.71% radiation efficiencies, respectively. The realized gain is 2.51, 3.70, and 5.46 dBi at frequencies 3, 8, and 11.32 GHz, respectively, with a peak gain of 5.46 dBi at 11.32 GHz. Specific absorption rate (SAR) values were tested using a human phantom and met FCC limits, confirming suitability for wearable and flexible IoT applications. The design was optimized using machine learning (ML), with KNN performing best, achieving 99.5% accuracy in S-parameter prediction. The measured and simulated results are correlated with each other for flat and bent antennas.

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Dr. Khemchandra Anuragi

Dr. Pinku Ranjan