DOA Estimation Based on Time-Frequency MUSIC Application to Massive MIMO Systems

被引：0

作者：

Hachad, Lamiae ^{[1
]}

Cherrak, Omar ^{[1
,2
,3
]}

Ghennioui, Hicham ^{[1
]}

Mrabti, Fatiha ^{[1
]}

Zouak, Mohcine ^{[1
]}

机构：

[1] Sidi Mohamed Ben Abdellah Univ, Fac Sci & Technol Fez, Signals Syst & Components Lab, Fes, Morocco

[2] Aix Marseille Univ, CNRS, ENSAM, LSIS,UMR 7296, F-13397 Marseille, France

[3] Univ Toulon & Var, CNRS, LSIS, UMR 7296, F-83957 La Garde, France

来源：

2017 3RD INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR SIGNAL AND IMAGE PROCESSING (ATSIP) | 2017年

关键词：

MIMO; Massive MIMO; DOA estimation; Time-Frequency Distributions; Joint Diagonalization; MUSIC; CELLULAR NETWORKS; SOURCE SEPARATION; DIAGONALIZATION; MATRICES;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this work, the problem of direction finding is addressed. We show the Direction Of Arrival (DOA) estimation can be realized through the non-unitary joint diagonalization of spatial quadratic time-frequency. We use an approach of selection of time-frequency points to construct the set of matrices which will be jointly diagonalized to estimate the noise subspace. The main advantage of this method is that it does not require any whitening stage, and thus, it is intended to work even with a class of correlated signals. Finally, the noise subspace obtained is then used to estimate the directions using the MUltiple Signal Classification MUSIC spectrum. Numerical simulations are provided in order to illustrate the effectiveness and the behavior of the proposed approach.

引用

页码：104 / 108

页数：5

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