A’isya Nur Aulia Yusuf, Prima Dewi Purnamasari, F. Zulkifli
{"title":"Gain Enhancement of Microstrip Antenna Using Genetic Algorithm: A Review","authors":"A’isya Nur Aulia Yusuf, Prima Dewi Purnamasari, F. Zulkifli","doi":"10.1109/ICRAMET53537.2021.9650491","DOIUrl":null,"url":null,"abstract":"In research on microstrip patch antennas, increasing antenna gain is a challenge. Various techniques have been carried out to increase the gain of microstrip antennas. However, most of the implementations of this method generally requires computer resources with high computing and storage space and takes a lot of time to run the simulation. Therefore, machine learning methods are used to optimize the antenna design to reduce the iteration process and increase antenna gain. Genetic algorithm is one of the efficient optimization methods and has been widely used in the electromagnetic field. This paper will review and compare the implementation of genetic algorithms in the microstrip antenna design process to improve antenna gain.","PeriodicalId":269759,"journal":{"name":"2021 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRAMET53537.2021.9650491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In research on microstrip patch antennas, increasing antenna gain is a challenge. Various techniques have been carried out to increase the gain of microstrip antennas. However, most of the implementations of this method generally requires computer resources with high computing and storage space and takes a lot of time to run the simulation. Therefore, machine learning methods are used to optimize the antenna design to reduce the iteration process and increase antenna gain. Genetic algorithm is one of the efficient optimization methods and has been widely used in the electromagnetic field. This paper will review and compare the implementation of genetic algorithms in the microstrip antenna design process to improve antenna gain.