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Large System Analysis of Power Normalization Techniques in Massive MIMO.

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Title: Large System Analysis of Power Normalization Techniques in Massive MIMO.
Authors: Sadeghi, Meysam1, Sanguinetti, Luca2, Couillet, Romain3, Yuen, Chau1
Source: IEEE Transactions on Vehicular Technology. Oct2017, Vol. 66 Issue 10, p9005-9017. 13p.
Subjects: Performance of MIMO systems, System analysis software, Channel estimation, Dynamic stability of electric power systems
Abstract: Linear precoding has been widely studied in the context of massive multiple-input multiple-output (MIMO) together with two common power normalization techniques, namely, matrix normalization (MN) and vector normalization (VN). Despite this, their effect on the performance of massive MIMO systems has not been thoroughly studied yet. The aim of this paper is to fulfill this gap by using large system analysis. Considering a system model that accounts for channel estimation, pilot contamination, arbitrary pathloss, and per-user channel correlation, we compute tight approximations for the signal-to-interference-plus-noise ratio and the rate of each user equipment in the system while employing maximum ratio transmission (MRT), zero forcing (ZF), and regularized ZF precoding under both MN and VN techniques. Such approximations are used to analytically reveal how the choice of power normalization affects the performance of MRT and ZF under uncorrelated fading channels. It turns out that ZF with VN resembles a sum rate maximizer while it provides a notion of fairness under MN. Numerical results are used to validate the accuracy of the asymptotic analysis and to show that in massive MIMO, noncoherent interference and noise, rather than pilot contamination, are often the major limiting factors of the considered precoding schemes. [ABSTRACT FROM PUBLISHER]
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Database: Engineering Source
Description
Abstract:Linear precoding has been widely studied in the context of massive multiple-input multiple-output (MIMO) together with two common power normalization techniques, namely, matrix normalization (MN) and vector normalization (VN). Despite this, their effect on the performance of massive MIMO systems has not been thoroughly studied yet. The aim of this paper is to fulfill this gap by using large system analysis. Considering a system model that accounts for channel estimation, pilot contamination, arbitrary pathloss, and per-user channel correlation, we compute tight approximations for the signal-to-interference-plus-noise ratio and the rate of each user equipment in the system while employing maximum ratio transmission (MRT), zero forcing (ZF), and regularized ZF precoding under both MN and VN techniques. Such approximations are used to analytically reveal how the choice of power normalization affects the performance of MRT and ZF under uncorrelated fading channels. It turns out that ZF with VN resembles a sum rate maximizer while it provides a notion of fairness under MN. Numerical results are used to validate the accuracy of the asymptotic analysis and to show that in massive MIMO, noncoherent interference and noise, rather than pilot contamination, are often the major limiting factors of the considered precoding schemes. [ABSTRACT FROM PUBLISHER]
ISSN:00189545
DOI:10.1109/TVT.2017.2704112