{"title":"一种低复杂度天线感知空间协方差矩阵估计方法","authors":"Shangbin Wu, Xiaoqing Zhang","doi":"10.1109/WCNCW.2019.8902497","DOIUrl":null,"url":null,"abstract":"This paper proposed a low-complexity antenna-la-aware (ALA) covariance matrix estimation method. In the estimation process, antenna layout is assumed known at the estimator. Using this information, the estimator finds antenna pairs with statistically equivalent covariance values and sets their covariance values to the average of covariance values of all these antenna pairs. ALA for both uniform linear array (ULA) and uniform planar array (UPA) is discussed. This method takes the benefit that covariance matrices do not have full degrees of freedom. Then, the proposed ALA covariance matrix method is applied to a multi-cell network. Simulations have demonstrated that the proposed method can provide better performance than the widely used viaQ method, with respect to mean square errors and downlink spectral efficiencies.","PeriodicalId":121352,"journal":{"name":"2019 IEEE Wireless Communications and Networking Conference Workshop (WCNCW)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Low-Complexity Antenna-La-Aware Spatial Covariance Matrix Estimation Method\",\"authors\":\"Shangbin Wu, Xiaoqing Zhang\",\"doi\":\"10.1109/WCNCW.2019.8902497\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposed a low-complexity antenna-la-aware (ALA) covariance matrix estimation method. In the estimation process, antenna layout is assumed known at the estimator. Using this information, the estimator finds antenna pairs with statistically equivalent covariance values and sets their covariance values to the average of covariance values of all these antenna pairs. ALA for both uniform linear array (ULA) and uniform planar array (UPA) is discussed. This method takes the benefit that covariance matrices do not have full degrees of freedom. Then, the proposed ALA covariance matrix method is applied to a multi-cell network. Simulations have demonstrated that the proposed method can provide better performance than the widely used viaQ method, with respect to mean square errors and downlink spectral efficiencies.\",\"PeriodicalId\":121352,\"journal\":{\"name\":\"2019 IEEE Wireless Communications and Networking Conference Workshop (WCNCW)\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Wireless Communications and Networking Conference Workshop (WCNCW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCNCW.2019.8902497\",\"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 IEEE Wireless Communications and Networking Conference Workshop (WCNCW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNCW.2019.8902497","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Low-Complexity Antenna-La-Aware Spatial Covariance Matrix Estimation Method
This paper proposed a low-complexity antenna-la-aware (ALA) covariance matrix estimation method. In the estimation process, antenna layout is assumed known at the estimator. Using this information, the estimator finds antenna pairs with statistically equivalent covariance values and sets their covariance values to the average of covariance values of all these antenna pairs. ALA for both uniform linear array (ULA) and uniform planar array (UPA) is discussed. This method takes the benefit that covariance matrices do not have full degrees of freedom. Then, the proposed ALA covariance matrix method is applied to a multi-cell network. Simulations have demonstrated that the proposed method can provide better performance than the widely used viaQ method, with respect to mean square errors and downlink spectral efficiencies.