Covariance Estimation with Projected Data: Applications to CSI Covariance Acquisition and Tracking

被引：0

作者：

Decurninge, Alexis ^{[1
]}

Guillaud, Maxime ^{[1
]}

机构：

[1] Huawei Technol, Math & Algorithm Sci Lab, Paris Res Ctr, 20 Quai Point Jour, F-92100 Boulogne Billancourt, France

来源：

2017 25TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO) | 2017年

关键词：

MAXIMUM-LIKELIHOOD; INCOMPLETE DATA; MASSIVE MIMO; EM ALGORITHM; SYSTEMS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We consider the problem of covariance estimation with projected or missing data, and in particular the application to spatial channel covariance estimation in a multi-user Massive MIMO wireless communication system with arbitrary (possibly time-varying and/or non-orthogonal) pilot sequences. We introduce batch and online estimators based on the expectation-maximization (EM) approach, and provide sufficient conditions for their asymptotic (for large sample sizes) unbiasedness. We analyze their application to both uplink and downlink Massive MIMO, and provide numerical performance benchmarks.

引用

页码：628 / 632

页数：5

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