{"title":"基于贝叶斯优化控制的分布式无线电力传输","authors":"M. Fujii","doi":"10.1109/WSCE49000.2019.9041071","DOIUrl":null,"url":null,"abstract":"Bayesian optimization is applied to antenna subset selection and transmit phase adjustment in distributed microwave power transfer. Both of the optimization controls are iteratively carried out based on energy feedback to maximize the received power in the low-complexity hardware configuration of massive antenna deployment. In addition, the computational complexity is reduced by exploiting the cyclic property of received power with respect to the transmit phase rotation. Our simulation results demonstrate that 95 percent of the maximum achievable received signal power was attained in 97 percent of the total trials by using 34 samples in both controls.","PeriodicalId":153298,"journal":{"name":"2019 2nd World Symposium on Communication Engineering (WSCE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Distributed Wireless Power Transfer Based on Bayesian-Optimized Control\",\"authors\":\"M. Fujii\",\"doi\":\"10.1109/WSCE49000.2019.9041071\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bayesian optimization is applied to antenna subset selection and transmit phase adjustment in distributed microwave power transfer. Both of the optimization controls are iteratively carried out based on energy feedback to maximize the received power in the low-complexity hardware configuration of massive antenna deployment. In addition, the computational complexity is reduced by exploiting the cyclic property of received power with respect to the transmit phase rotation. Our simulation results demonstrate that 95 percent of the maximum achievable received signal power was attained in 97 percent of the total trials by using 34 samples in both controls.\",\"PeriodicalId\":153298,\"journal\":{\"name\":\"2019 2nd World Symposium on Communication Engineering (WSCE)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 2nd World Symposium on Communication Engineering (WSCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WSCE49000.2019.9041071\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 2nd World Symposium on Communication Engineering (WSCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSCE49000.2019.9041071","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distributed Wireless Power Transfer Based on Bayesian-Optimized Control
Bayesian optimization is applied to antenna subset selection and transmit phase adjustment in distributed microwave power transfer. Both of the optimization controls are iteratively carried out based on energy feedback to maximize the received power in the low-complexity hardware configuration of massive antenna deployment. In addition, the computational complexity is reduced by exploiting the cyclic property of received power with respect to the transmit phase rotation. Our simulation results demonstrate that 95 percent of the maximum achievable received signal power was attained in 97 percent of the total trials by using 34 samples in both controls.
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