Multi-Band Antenna Design Optimization Using Nature-Inspired Evolutionary Algorithm for 5G Wireless Communication

Abstract

Automation and telecommunication systems are increasingly improving and becoming more easily integrated thanks to wireless communication technology, in which the essential component is the antenna. Designing and optimizing antenna structures still takes a lot of time, especially for complex structures with multiple operating frequency bands or complex material layers. With modern computing power, the speed of computation is increasingly efficient, and combining automated computation for optimization and design is entirely feasible. Many research groups around the world have implemented automated antenna design through optimization algorithms, genetic algorithms, swarm algorithms, collectively referred to as evolutionary algorithms. These algorithms simplify the antenna design process, making it more automated and optimized. In this paper, the Improved Black Hole algorithm is proposed and used to optimize the design of a CPW-Fed slot microstrip antenna.