Applying genetic algorithm for optimizing return loss of proximity coupled microstrip antenna

Abstract

The proximity-coupled rectangular microstrip antenna (PRMSA) is optimized using the genetic algorithm (GA) to improve key parameters such as input impedance, return loss, and voltage standing wave ratio (VSWR). Fitness functions for the GA program have been developed using the transmission-line method (TLM) to analyze the PRMSA. The stochastic search capabilities of GA address electromagnetic characteristics that are challenging for other optimization techniques. In this study, GA optimization technique has been utilized for the PRMSA; this antenna is optimized for its parameters as length of the patch, thickness, width and length of strip line in order to achieve better return loss. According to the existing results for calculating S11, we arrived at the smallest and best value (-28 dB) using GA compared to previous works using other methods. Further analysis is provided on how various antenna parameters affect performance. The GA was executed for 100 generations, with the optimized results enhancing the antenna’s efficiency. The computed results closely match the experimental data, and the accuracy of these results supports the effectiveness of using GA.