Paper Info
Title
PCA-Based Channel Estimation and Tracking for Massive MIMO Systems With Uniform Rectangular Arrays
Abstract
In this paper, a fast adaptive Principal Component Analysis (PCA) based scheme is proposed to estimate and track the channel state information (CSI) of two dimensional (2D) massive multiple-input and multiple-output (M-MIMO) systems with uniform rectangular array (URA). First, the signals received online at the base station (BS) are used to estimate and track the principal components. Then, based on the estimated signal eigenvectors, a 2D unitary estimating signal parameters via rotational invariance technique (ESPRIT) algorithm is introduced to jointly estimate and track the channel coefficients which include the direction of arrival (DoA) of elevation and azimuth angles and the channel gain corresponding to each resolvable path of the channel. In order to improve the tracking speed, an optimal step size is derived which can accelerate the convergence speed of channel tracking significantly. Since the 2D unitary ESPRIT algorithm is applied, the proposed method can reduce computational complexity by converting the complex data matrix to the real one. Simulation results are provided to verify the estimation and tracking accuracy of the proposed scheme.
Year
DOI
Venue
2020
10.1109/TWC.2020.3006042
IEEE Transactions on Wireless Communications
Keywords
DocType
Volume
2D massive MIMO systems,3D channel estimation,direction of arrival(DoA),PCA,2D unitary ESPRIT
Journal
19
Issue
ISSN
Citations 
10
1536-1276
2
PageRank 
References 
Authors
0.37
0
3
Name
Order
Citations
PageRank
Anding Wang1567.00
Rui Yin21107.52
Caijun Zhong32007120.77