Nature Inspired optimization algorithms for Quasi Yagi antenna design for IoT and future wireless communications

Abstract

The rapid development of the Internet of Things (IoT) and the 6G newlinecommunication environment requires an effective antenna design to support newlinehigh-frequency communication. The antenna design needs optimized newlineparameters such as impedance matching, bandwidth, gain, and polarization to newlinemeet the communication standards. Conventional antenna design tools and newlinetechniques are incorporated into antenna design, but methods face newlinecomputation and multi-dimensional and complex parameter issues, which newlinereduces the overall antenna efficiency. The research issue is addressed by newlinecombining nature-inspired optimization algorithms with antenna design to newlineovercome complex problems. newlineThis research work uses the Fireflies Optimization Algorithm newline(FOA), Brainstorm Optimization Algorithm (BOA) and Lion Optimization newlineAlgorithm (LOA) to finetune the antenna parameters. These optimization newlinealgorithms concentrate on the antenna design to improve their performance newlineand minimizing the computational overheads. Therefore, the main objective newlineof this research is to improve the antenna gain, good impedance matching and newlineminimum reflection coefficient. During the analysis, the optimization newlinealgorithm uses its search criteria, and the obtained solutions are evaluated newlinewith the objective function to predict the optimum solution. newline