Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays

Rusek, Fredrik; Persson, Daniel; Lau, Buon Kiong; Larsson, Erik G.; Marzetta, Thomas L.; Tufvesson, Fredrik

doi:10.1109/msp.2011.2178495

Cited by 4,802 publications

(3,773 citation statements)

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“…Massive MIMO, where the BS includes a very large number of antennas, have emerged as one of the most promising technologies towards this direction because more degrees of freedom and increased power efficiency are achieved by simplifying multi-user processing, reducing transmit power, as well as vanishing the effects of thermal noise and fast fading [5]- [16]. Along these lines, given a multi-cellular scenario, linear detectors and precoders behave nearly optimal as the number of BS antennas goes to infinity, taking into account that channel vectors tend to be orthogonal when the number of antennas is large [7].…”

Section: Introductionmentioning

confidence: 99%

Deterministic Equivalent Performance Analysis of Time-Varying Massive MIMO Systems

Papazafeiropoulos

Ratnarajah

2015

IEEE Trans. Wireless Commun.

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Abstract-Delayed channel state information at the transmitter (CSIT) due to time variation of the channel, coming from the users' relative movement with regard to the BS antennas, is an inevitable degrading performance factor in practical systems. Despite its importance, little attention has been paid to the literature of multi-cellular multiple-input massive multiple-output (MIMO) system by investigating only the maximal ratio combining (MRC) receiver and the maximum ratio transmission (MRT) precoder. Hence, the contribution of this work is designated by the performance analysis/comparison of/with more sophisticated linear techniques, i.e., a minimum-mean-square-error (MMSE) detector for the uplink and a regularized zero-forcing (RZF) precoder for the downlink are assessed. In particular, we derive the deterministic equivalents of the signal-to-interference-plus-noise ratios (SINRs), which capture the effect of delayed CSIT, and make the use of lengthy Monte Carlo simulations unnecessary. Furthermore, prediction of the current CSIT after applying a Wiener filter allows to evaluate the mitigation capabilities of MMSE and RZF. Numerical results depict that the proposed achievable SINRs (MMSE/RZF) are more efficient than simpler solutions (MRC/MRT) in delayed CSIT conditions, and yield a higher prediction at no special computational cost due to their deterministic nature. Nevertheless, it is shown that massive MIMO are preferable even in time-varying channel conditions.

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Section: Introductionmentioning

confidence: 99%

Deterministic Equivalent Performance Analysis of Time-Varying Massive MIMO Systems

Papazafeiropoulos

Ratnarajah

2015

IEEE Trans. Wireless Commun.

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“…where H is the M × K matrix with i.i.d entries [4], representing the small-scale fading between the K users and the BS, and the entry h mk is a circular symmetric complex Gaussian (CSCG) random variable with zero mean and unit variance, i.e., h mk ∼ CN (0, 1); D is a K × K diagonal matrix of the large-scale path-loss with…”

Section: Channel Modelmentioning

confidence: 99%

“…Similar to channel matrix G, random matrixG s can be expressed as [4], and so do the vectors of the SI channel matrix. We then have…”

Section: Channel Modelmentioning

confidence: 99%

Self-interference suppression with imperfect channel estimation in a shared-antenna full-duplex massive MU-MIMO system

Xing

Liu

Zhai

et al. 2017

J Wireless Com Network

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In this paper, we consider a shared-antenna full-duplex massive MU-MIMO system and prove that the self-interference (SI) at the base station (BS) can be suppressed, though the direct-path SI exists and the signal/SI channel is imperfectly estimated. The BS is assumed to employ zero-forcing (ZF) or maximal-ratio transmission/maximal-ratio combining (MRT/MRC) method to linearly process signals. We propose a precoded SI channel training scheme by employing orthogonal sequences and downlink precoding, so the SI channel can be estimated like the signal channel with a much lower dimension. Based on the channel estimation, we further analyze the SI suppression by combining the SI removal and the large-scale antenna linear processing (LALP) method. Numerical results show that an additional 36 dB SI can be suppressed by combining the SI removal and the LALP suppression. We derive the tight closed-form lower bounds of the achievable rates for the combined suppression. Finally, we maximize the system spectral efficiency and energy efficiency based on the simulation and closed-form approximations.

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“…To meet the increasing demand for wireless broadband services from fast-growing mobile users over the next decade, a potential technology termed massive MIMO (Rusek et al 2013) (also known as large-scale MIMO, full-dimension MIMO, or hyper-MIMO) has emerged to further reap the benefits of utilising multiple antenna technology and promises orders-ofmagnitude improvements in spectral-efficiency over 4G LTE-Advanced. With a large number of antennas (possibly hundreds or even thousands) at the wireless transmitter, the massive MIMO technology can not only improve link reliability, but also increase the radiated energy efficiency due to significant array gains (Ngo et al 2013).…”

Section: Massive Mimo -A Solution To the Spectrum Crunchmentioning

confidence: 99%

Towards 5th generation cellular mobile networks

Zhang¹,

Cheng²,

Weily³

et al. 2014

ajTDE

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SummaryCellular mobile networks have enabled ubiquitous communications and largely changed the way we live and work. At the same time, the network itself has been undergoing significant changes in the process of meeting our ever increasing demands on data rate and quality of service. In this article, we show the path of the evolution in both standards and techniques, and provide our vision for the future of the cellular networks. We review the evolution of international standards for cellular mobile networks in the last two decades, describe how the network layout has been migrating from rigid cellular architecture to random and dense small cells, and provide an indepth discussion on potential enabling techniques for the next generation (5G) cellular networks, particularly massive MIMO and multiband base-station antennas.

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Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays

Cited by 4,802 publications

References 50 publications

Deterministic Equivalent Performance Analysis of Time-Varying Massive MIMO Systems

Deterministic Equivalent Performance Analysis of Time-Varying Massive MIMO Systems

Self-interference suppression with imperfect channel estimation in a shared-antenna full-duplex massive MU-MIMO system

Towards 5th generation cellular mobile networks

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