Linear Massive MIMO Precoders in the Presence of Phase Noise – A Large-Scale Analysis
Journal article, 2016

We study the impact of phase noise on the downlink performance of a multi-user multiple-input multiple-output system, where the base station (BS) employs a large number of transmit antennas M. We consider a setup where the BS employs Mosc free-running oscillators, and M/Mosc antennas are connected to each oscillator. For this configuration, we analyze the impact of phase noise on the performance of the regularized zero-forcing (RZF), when M and the number of users K are asymptotically large, while the ratio M/K=β is fixed. We analytically show that the impact of phase noise on the signal-to-interference-plus-noise ratio (SINR) can be quantified as an effective reduction in the quality of the channel state information available at the BS when compared to a system without phase noise. As a consequence, we observe that as Mosc increases, the SINR performance of all considered precoders degrades. On the other hand, the variance of the random phase variations caused by the BS oscillators reduces with increasing Mosc. Through Monte-Carlo simulations, we verify our analytical results, and compare the performance of the precoders for different phase noise and channel noise variances. For all considered precoders, we show that when β is small, the performance of the setup where all BS antennas are connected to a single oscillator is superior to that of the setup where each BS antenna has its own oscillator. However, the opposite is true when β is large and the signal-to-noise ratio at the users is low.

phase noise

linear precoding

multi-user MIMO.

Massive MIMO

broadcast channel

random matrix theory


Rajet Krishnan

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

M Reza Khanzadi

Chalmers, Microtechnology and Nanoscience (MC2), Microwave Electronics

N. Krishnan

Qualcomm Technologies

Y. Wu

University of Erlangen-Nuremberg (FAU)

Alexandre Graell i Amat

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

Thomas Eriksson

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

R. Schober

University of Erlangen-Nuremberg (FAU)

IEEE Transactions on Vehicular Technology

0018-9545 (ISSN) 1939-9359 (eISSN)

Vol. 65 5 3057-3071 7116610

Signal Recovery: Compressed Sensing meets Coding Theory

Swedish Research Council (VR) (2011-5961), 2012-01-01 -- 2015-12-31.

Areas of Advance

Information and Communication Technology

Subject Categories


Communication Systems

Signal Processing



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9/6/2018 1