Eiji Ninomiya, M. Yukawa, Renato L. G. Cavalcante, Lorenzo Miretti
{"title":"Estimation of Angular Power Spectrum Using Multikernel Adaptive Filtering","authors":"Eiji Ninomiya, M. Yukawa, Renato L. G. Cavalcante, Lorenzo Miretti","doi":"10.23919/APSIPAASC55919.2022.9980067","DOIUrl":null,"url":null,"abstract":"This paper addresses the problem of estimating the angular power spectrum (APS) of massive multiple input multiple output wireless channels. Estimating the APS is useful, for instance, for simplifying the downlink channel estimation problem in frequency division duplex systems. We propose an efficient online algorithm that estimates the APS from the channel spatial covariance matrix. The proposed algorithm approximates the APS as a sum of Gaussian functions and leverages the framework of multikernel adaptive filtering.","PeriodicalId":382967,"journal":{"name":"2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/APSIPAASC55919.2022.9980067","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper addresses the problem of estimating the angular power spectrum (APS) of massive multiple input multiple output wireless channels. Estimating the APS is useful, for instance, for simplifying the downlink channel estimation problem in frequency division duplex systems. We propose an efficient online algorithm that estimates the APS from the channel spatial covariance matrix. The proposed algorithm approximates the APS as a sum of Gaussian functions and leverages the framework of multikernel adaptive filtering.