Design and Optimization of Microstrip Antenna for 5G Wireless Applications using Genetic Algorithm
Muhammed Sheriff S.
Department of Electrical and Electronics Engineering, University of Uyo, Uyo, Nigeria.
Obot Akaninyene B. *
Department of Electrical and Electronics Engineering, University of Uyo, Uyo, Nigeria.
Udofia Kufre M.
Department of Electrical and Electronics Engineering, University of Uyo, Uyo, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
The need for small-sized communication devices has compelled designers to create antennas with compact dimensions. These antennas have to meet certain specifications, including being inexpensive, lightweight, easy to install, and built with a robust mechanical structure. In this report, two microstrip antennas operating at 28 GHz-one unoptimized and the other optimized—are designed, simulated, analyzed, and compared. The design of the unoptimized antenna was done in Ansoft HFSS, while Genetic Algorithm (GA) optimization was done in MATLAB. Results obtained make it clear how return loss, impedance bandwidth, gain, directivity, and VSWR relate to one another. The main parameters that determine the performance characteristics of the antenna are the patch width (Wp), the width (Wf) of the microstrip line, and the relative permittivity (\(\varepsilon{r}\)) of the dielectric material under the patch. These conclusions were confirmed based on design calculations and simulated results. Findings revealed that the optimized antenna worked better at 28 GHz than the unoptimized antenna, obtaining a larger impedance bandwidth (more than 63%), a 34% higher antenna gain (7.94 dBi against 5.25 dBi), and a 35% smaller footprint. The success indicators provided in the findings have helped to achieve the objectives of the study. Furthermore, a comparison study was carried out between the recommended antennas and a few previously published research.
Keywords: Genetic Algorithm, microstrip antenna, optimization, bandwidth, communication