{"title":"阵列网络上扩散降阶自适应的波束协调","authors":"Jinghua Li, W. Xia","doi":"10.23919/Eusipco47968.2020.9287332","DOIUrl":null,"url":null,"abstract":"In this work, we consider a distributed reduced-rank beam coordination problem over array networks. We develop an inherently adaptive combination scheme based on combination matrix for beam coordination problem. Two adaptive efficient implementation strategies for diffusion reduced-rank beamforming are proposed. Illustrative simulations validate that the proposed distributed reduced-rank adaptive algorithms could remarkably improve the convergence speed in comparison with the existing techniques under the condition of small samples.","PeriodicalId":6705,"journal":{"name":"2020 28th European Signal Processing Conference (EUSIPCO)","volume":"15 1","pages":"1822-1826"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Beam Coordination Via Diffusion Reduced-Rank Adaptation Over Array Networks\",\"authors\":\"Jinghua Li, W. Xia\",\"doi\":\"10.23919/Eusipco47968.2020.9287332\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we consider a distributed reduced-rank beam coordination problem over array networks. We develop an inherently adaptive combination scheme based on combination matrix for beam coordination problem. Two adaptive efficient implementation strategies for diffusion reduced-rank beamforming are proposed. Illustrative simulations validate that the proposed distributed reduced-rank adaptive algorithms could remarkably improve the convergence speed in comparison with the existing techniques under the condition of small samples.\",\"PeriodicalId\":6705,\"journal\":{\"name\":\"2020 28th European Signal Processing Conference (EUSIPCO)\",\"volume\":\"15 1\",\"pages\":\"1822-1826\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 28th European Signal Processing Conference (EUSIPCO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/Eusipco47968.2020.9287332\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 28th European Signal Processing Conference (EUSIPCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/Eusipco47968.2020.9287332","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Beam Coordination Via Diffusion Reduced-Rank Adaptation Over Array Networks
In this work, we consider a distributed reduced-rank beam coordination problem over array networks. We develop an inherently adaptive combination scheme based on combination matrix for beam coordination problem. Two adaptive efficient implementation strategies for diffusion reduced-rank beamforming are proposed. Illustrative simulations validate that the proposed distributed reduced-rank adaptive algorithms could remarkably improve the convergence speed in comparison with the existing techniques under the condition of small samples.