An Improved Dropping Algorithm for Line-of-Sight Massive MIMO With Max-Min Power Control

Farsaei, Amirashkan; Alvarado, Alex; Willems, F.M.J.; Gustavsson, Ulf

doi:10.1109/lcomm.2019.2912601

Cited by 13 publications

(9 citation statements)

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“…The reduction of the sum-rate due to the high correlation is considerable for LOS environments with max-min power control as reported in [5], [6] (max-min power control is used to provide uniformly good service for the users as reported in [3]). In addition, it is shown in [5,Fig. 2] that when there is only one pair of highly correlated users, the signal to noise ratio with max-min power control will drop significantly.…”

Section: Introductionmentioning

confidence: 99%

“…2] that when there is only one pair of highly correlated users, the signal to noise ratio with max-min power control will drop significantly. To deal with highly correlated scenarios in LOS environments with max-min power control, [3], [5], [6] studied dropping algorithms. However, dropping users may not be desirable in the case of latency-sensitive communication.…”

Section: Introductionmentioning

confidence: 99%

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Uniform Linear Arrays With Optimized Inter-Element Spacing for LOS Massive MIMO

et al. 2021

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Uniform Linear Arrays With Optimized Inter-Element Spacing for LOS Massive MIMO

et al. 2021

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“…which incorporates the small-scale fading effect. In [7] it is shown that how the sum-rate of a MU-MIMO system is being decreased as the correlation among two users increases, while linear precoders are applied. The normalized spatial correlation between two users can be computed by:…”

Section: Nlos Channel Model and Spatial Correlationmentioning

confidence: 99%

Array Configuration Effect on the Spatial Correlation of MU-MIMO Channels in NLoS Environments

Amani

Farsaei

Gustavsson

et al. 2020

2020 14th European Conference on Antennas and Propagation (EuCAP)

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In this paper, three different base-station antenna (BSA) configurations are compared in terms of inter-user spatial correlation in a two dimensional (2D) non-line-of-sight (NLoS) environment. The three configurations are: (i) a regular uniform linear array (ULA); (ii) a periodic sparse array; and (iii) an aperiodic sparse array. Electromagnetic modeling of the NLoS channel is proposed where scatterers are considered as resonant dipoles confined in clusters of scatterers (CoSs). While the probability of facing highly correlated user-equipments (UEs) in a multiuser multiple-input multiple-output (MU-MIMO) system is decreasing as the richness of mutipath increases, the sparsity (increased inter-element spacing) is seen to be capable of reducing this probability as well. This is due to the larger spatial variations experienced by the sparse array. Moreover, the results show that further improvement can be achieved by deploying an aperiodic distribution of antenna elements into the sparse antenna aperture.

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“…In this section, THP with two power allocation schemes is reviewed. The THP sum-rates of the two power allocation schemes are derived for a "correlated channel of size K" defined in [8,Definition 1]. In this type of channel, user K −1 and user K are the only correlated pair of users.…”

Section: System Model and Preliminariesmentioning

confidence: 99%

“…A similar criterion was used in [6], [7]. Instead of simulationbased thresholds as in [3], thresholds are derived in [8] for CB and ZF with max-min power control.…”

Section: Introductionmentioning

confidence: 99%

An Improved Dropping Algorithm for Line-of-Sight Massive MIMO With Tomlinson–Harashima Precoding

et al. 2019

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One of the problems in line-of-sight massive MIMO is that a few users can have correlated channel vectors. To alleviate this problem, a dropping algorithm has been proposed in the literature, which drops some of the correlated users to make the spatial correlation among the remaining users be less than a certain threshold. Thresholds were found by running a large number of simulations. In this paper, the same dropping algorithm is analyzed for a known nonlinear precoder: Tomlinson-Harashima precoder. Instead of simulationbased thresholds, closed-form analytical expressions are derived in this paper for two power allocation schemes: max-min and equal received power control schemes. It is shown that the derived thresholds are optimal in terms of achievable sum-rate when there is only one correlated pair of users. For channels with multiple pairs of correlated users, simulation results show that using the derived thresholds improves the 5th percentile sumrate. Due to the fairness criterion of max-min, the improvement for max-min power control is much higher than equal received power control.Index Terms-Correlated users, line-of-sight, massive MIMO, max-min power control, Tomlinson-Harashima precoding.1 Lowercase, bold lowercase, and bold uppercase letters denote scalars, column vectors, and matrices, respectively. | · | and · denote the absolute value and l 2 -norm operators. The superscripts * , T , and H denote complex conjugate, un-conjugated transpose, and conjugated transpose, respectively. diag(p) denotes a diagonal matrix with diagonal entries taken from p. This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication.The final version of record is available at http://dx.

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An Improved Dropping Algorithm for Line-of-Sight Massive MIMO With Max-Min Power Control

Cited by 13 publications

References 10 publications

Uniform Linear Arrays With Optimized Inter-Element Spacing for LOS Massive MIMO

Uniform Linear Arrays With Optimized Inter-Element Spacing for LOS Massive MIMO

Array Configuration Effect on the Spatial Correlation of MU-MIMO Channels in NLoS Environments

An Improved Dropping Algorithm for Line-of-Sight Massive MIMO With Tomlinson–Harashima Precoding

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