Cluster Characterization of 3-D MIMO Propagation Channel in an Urban Macrocellular Environment

Sangodoyin, Seun; Kristem, Vinod; Bas, C. Umit; Käske, Martin; Lee, Juho; Schneider, Christian; Sommerkorn, Gerd; Zhang, Charlie Jianzhong; Molisch, Andreas F.

doi:10.1109/twc.2018.2837088

Cited by 39 publications

(60 citation statements)

References 58 publications

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“…IV. In particular, following [12] for the types of distributions used, we assume a wrapped Gaussian for the central azimuth angle, φ c,s values. We consider the following two scenarios.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…We consider the following two scenarios. Scenario 1, representing a relatively sparse channel with a narrow angular spread, is based on the recent measurement data in [12]. From [12] we use the values of Γ, σ sf , C, S, σ c , σ s and the lower 10% values of the lognormally distributed values ofσ c andσ s .…”

Section: Numerical Resultsmentioning

confidence: 99%

“…In this study, we do not consider per-element antenna patterns in the azimuth and elevation domains, since we would like to remove the directional dependence of the elements in order to evaluate the performance upper bound of linear processors. We note that this assumption does not affect the resulting propagation parameters used for further evaluation in the paper, since the majority of the measurements are post processed with high resolution parameter extraction techniques like RiMAX and SAGE in [12], [33], where a double-directional channel response is created from the measured parameters to remove the antenna dependence from the channel measurements, i.e., to make the propagation parameters antenna agnostic.…”

Section: A Channel Modelmentioning

confidence: 99%

“…(2) they have a direct link to the antenna layout at both link ends, and to the propagation environment; (3) they are applicable over a wide range of frequency bands. For example, recent ray-based measurements are used to characterize the channel at 2.53 GHz [12] and at 28 GHz and 73 GHz [13]- [15]. For these reasons, ray-based channels form the basis of many standardized models used to evaluate the performance of the upcoming new radio systems [16].…”

mentioning

confidence: 99%

“…In practice, such simple distributions are rarely observed. For instance, recent measurement data [12] has shown that the ray angles in azimuth and elevation domains across multiple clusters are Gaussian and Laplacian distributed, respectively, whereas angles within a cluster are well described by Laplacian distributions. 3GPP channel models [16] also follow a similar form with more complex statistical distributions, which are not treated in the prior state-of-the-art [26]- [30] due to the underlying mathematical complexities.…”

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confidence: 99%

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Analytical Framework for Full-Dimensional Massive MIMO With Ray-Based Channels

Miller

Smith

Dmochowski

et al. 2019

IEEE J. Sel. Top. Signal Process.

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The performance of baseband beamforming in multiuser multiple-input multiple-output (MU-MIMO) systems has been extensively studied for simplified statistical channel models where no angular parameters are taken into account. In contrast, there is little performance analysis with ray-based models, which are more physically motivated, feature prominently in standardization and have been experimentally validated. Thus, unlike previous studies, we present a mathematical framework to analyze the performance of zero forcing (ZF) and minimum mean-squared error (MMSE) combining. Using a central result for averaging in the angular domain, we derive tight approximations for the uplink signal-to-noise ratio and signal-to-interference-and-noise ratio (SINR) for ZF and MMSE processing, respectively, and the resulting spectral efficiencies. The remarkably simple expressions offer the following insights into the effects of the propagation environment. We demonstrate an improvement in performance when moving from vertical uniform rectangular array (URA) to horizontal URA to uniform linear array (ULA) antenna configurations. There is also a corresponding increase in the robustness of the performance to propagation scenarios. We demonstrate that under specific conditions increasing the angular spread can decrease the SINR for a ULA-an unexpected behavior which we link to the effects of end-fire radiation. Furthermore, our results allow us to investigate the impact of different array configurations and system parameters on the rate of convergence to favorable propagation conditions. Finally, we evaluate the spatial correlation properties intrinsically present in ray-based models, and compare them to the commonly used simple exponential model which yields equal, fixed correlation characteristics for each user. Index Terms-Ergodic spectral efficiency, favorable propagation, linear processing, MU-MIMO, ray-based channel models. I. INTRODUCTION Performance analysis of linear transceiver techniques for conventional and massive multiuser multiple-input multipleoutput (MU-MIMO) systems is well advanced for simple statistical channel models [2]-[7]. Early work on independent, identically distributed Rayleigh fading channels has been extended to a wide range of more complex and realistic channel C. L. Miller and P. A. Dmochowski are with the School of Engineering and Computer Science,

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“…IV. In particular, following [12] for the types of distributions used, we assume a wrapped Gaussian for the central azimuth angle, φ c,s values. We consider the following two scenarios.…”

Section: Numerical Resultsmentioning

confidence: 99%

Section: Numerical Resultsmentioning

confidence: 99%