4 research outputs found

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

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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 multi-user 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

    An improved dropping algorithm for line-of-sight massive MIMO with max-min power control

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    \u3cp\u3eIn line-of-sight massive MIMO, there is a nonnegligible probability that two users become highly correlated, which leads to a reduction in the achievable sum-rates of linear precoders. In this letter, threshold values of a previously proposed dropping algorithm are found analytically to avoid repeating a large number of simulations to find the optimal threshold. These thresholds allow us to improve conjugate beamforming (CB) and zero-forcing (ZF) sum-rates with max-min power control. By using the proposed threshold values, the CB and ZF sum-rates are maximized, when there are only two correlated users. In addition, by using the derived thresholds, a modified dropping algorithm is proposed for channels with any number of correlated users. The results of the simulation scenarios show that at signal to noise ratio of 20 dB and 120 antennas at the base station, the modified algorithm improves the average CB and ZF sum-rates up to 36% and 5%, respectively.\u3c/p\u3

    An improved dropping algorithm for line-of-sight massive MIMO with max-min power control

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    In line-of-sight massive MIMO, there is a nonnegligible probability that two users become highly correlated, which leads to a reduction in the achievable sum-rates of linear precoders. In this letter, threshold values of a previously proposed dropping algorithm are found analytically to avoid repeating a large number of simulations to find the optimal threshold. These thresholds allow us to improve conjugate beamforming (CB) and zero-forcing (ZF) sum-rates with max-min power control. By using the proposed threshold values, the CB and ZF sum-rates are maximized, when there are only two correlated users. In addition, by using the derived thresholds, a modified dropping algorithm is proposed for channels with any number of correlated users. The results of the simulation scenarios show that at signal to noise ratio of 20 dB and 120 antennas at the base station, the modified algorithm improves the average CB and ZF sum-rates up to 36% and 5%, respectively

    Serving Correlated Users in Line-of-Sight Massive MIMO Systems for 5G and Beyond

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