Image Classifier Based Generative Method for Planar Antenna Design

Designing antennas in the wireless consumer electronic industry is a technical challenge that requires not only many efforts in simulation and measurement, but also experience in developing initial prototypes. The antenna space and the surrounding environment keep changing within various products. A well-designed antenna that meets the target of one product may not work with another even though they might come from the same production line. Selecting an initial antenna type, a monopole, loop or inverted F, to start with is critical. In many cases, it depends on who is the antenna engineer working on this project. For a same project and given the same specifications, different antenna engineers might surprisingly come out unalike types of antenna designs just because of their personalized experience and taste. In this era of rapid product iterations, there is high demand of creative antenna designs and it is hard to find antenna expertise. Therefore, in this paper, we will present a workflow of proposing good prototypes that antenna design experience is not a mandatory requirement. Antenna optimization have been widely studied and well presented in previous work, such as the trust region method Koziel and Unnsteinsson [2018], particle swarm method Jin and Rahmat-Samii [2007], evolutionary strategies Liu et al. [2014] and many types of machine learning methods Sharma et al. [2020], Koziel et al. [2021], Nan et al. [2021], This project is sponsored by Meta Internship Program.