{"title":"基于凸优化的数字超材料相位编码框架","authors":"Zhen Zhang, Junwei Zhang, Junwei Wu, Q. Cheng, Q. Cheng","doi":"10.1109/iwem53379.2021.9790523","DOIUrl":null,"url":null,"abstract":"Accurate phase coding is a key to meet the demand of practical problems for digital metamaterials. In this work, we propose a novel phase coding method based on convex optimization for digital metamaterials. A general nonconvex problem of metamaterials beam synthesis is reformulated into a convex optimization problem. The quasi-Newton optimization method is used to obtain the solution of the convex optimization problem. Then a shortest-distance discretization method maps the obtained solution into a selectable phase. A digital metamaterials example is presented to demonstrate the performance of the proposed method in comparison with conventional genetic algorithm.","PeriodicalId":141204,"journal":{"name":"2021 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Phase Coding Framework of Digital Metamaterials Based on Convex Optimization\",\"authors\":\"Zhen Zhang, Junwei Zhang, Junwei Wu, Q. Cheng, Q. Cheng\",\"doi\":\"10.1109/iwem53379.2021.9790523\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Accurate phase coding is a key to meet the demand of practical problems for digital metamaterials. In this work, we propose a novel phase coding method based on convex optimization for digital metamaterials. A general nonconvex problem of metamaterials beam synthesis is reformulated into a convex optimization problem. The quasi-Newton optimization method is used to obtain the solution of the convex optimization problem. Then a shortest-distance discretization method maps the obtained solution into a selectable phase. A digital metamaterials example is presented to demonstrate the performance of the proposed method in comparison with conventional genetic algorithm.\",\"PeriodicalId\":141204,\"journal\":{\"name\":\"2021 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iwem53379.2021.9790523\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition (iWEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iwem53379.2021.9790523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Phase Coding Framework of Digital Metamaterials Based on Convex Optimization
Accurate phase coding is a key to meet the demand of practical problems for digital metamaterials. In this work, we propose a novel phase coding method based on convex optimization for digital metamaterials. A general nonconvex problem of metamaterials beam synthesis is reformulated into a convex optimization problem. The quasi-Newton optimization method is used to obtain the solution of the convex optimization problem. Then a shortest-distance discretization method maps the obtained solution into a selectable phase. A digital metamaterials example is presented to demonstrate the performance of the proposed method in comparison with conventional genetic algorithm.