Spatial Correlation Characterization of a Full Dimension Massive MIMO System
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Online Publication Date2017-02-07
Print Publication Date2016-12
Permanent link to this recordhttp://hdl.handle.net/10754/623911
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AbstractElevation beamforming and Full Dimension MIMO (FD-MIMO) are currently active areas of research and standardization in 3GPP LTE-Advanced. FD-MIMO utilizes an active antenna array system (AAS), that provides the ability of adaptive electronic beam control over the elevation dimension, resulting in a better system performance as compared to the conventional 2D MIMO systems. FD-MIMO is more advantageous when amalgamated with massive MIMO systems, in that it exploits the additional degrees of freedom offered by a large number of antennas in the elevation. To facilitate the evaluation of these systems, a large effort in 3D channel modeling is needed. This paper aims at providing a summary of the recent 3GPP activity around 3D channel modeling. The 3GPP proposed approach to model antenna radiation pattern is compared with the ITU approach. A closed-form expression is then worked out for the spatial correlation function (SCF) for channels constituted by individual antenna elements in the array by exploiting results on spherical harmonics and Legendre polynomials. The proposed expression can be used to obtain correlation coefficients for any arbitrary 3D propagation environment. Simulation results corroborate and study the derived spatial correlation expression. The results are directly applicable to the analysis of future 5G 3D massive MIMO systems.
CitationNadeem Q-U-A, Kammoun A, Debbah M, Alouini M-S (2016) Spatial Correlation Characterization of a Full Dimension Massive MIMO System. 2016 IEEE Global Communications Conference (GLOBECOM). Available: http://dx.doi.org/10.1109/glocom.2016.7842281.
SponsorsThe work of Q.-U.-A. Nadeem, A. Kammoun and M. -S. Alouini was supported by a CRG 3 grant from the Office of Sponsored Research at KAUST. The work of M´erouane Debbah was supported by ERC Starting Grant 305123 MORE (Advanced Mathematical Tools for Complex Network Engineering).