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Simulation code for “Hardware Distortion Correlation Has Negligible Impact on UL Massive MIMO Spectral Efficiency” by Emil Björnson, Luca Sanguinetti, and Jakob Hoydis, IEEE Transactions on Communications, To appear
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README.md
functionRlocalscatteringApprox.m
quantizationLevels.mat
simulationFigure10.m
simulationFigure11.m
simulationFigure12.m
simulationFigure2.m
simulationFigure3.m
simulationFigure4.m
simulationFigure5.m
simulationFigure6.m
simulationFigure7.m
simulationFigure8.m
simulationFigure9.m

README.md

Hardware Distortion Correlation Has Negligible Impact on UL Massive MIMO Spectral Efficiency

This is a code package is related to the follow scientific article:

Emil Bjornson, Luca Sanguinetti, Jakob Hoydis, “Hardware Distortion Correlation Has Negligible Impact on UL Massive MIMO Spectral Efficiency,” IEEE Transactions on Communications, to appear.

The package contains a simulation environment, based on Matlab, that reproduces some of the numerical results and figures in the article. We encourage you to also perform reproducible research!

Abstract of Article

This paper analyzes how the distortion created by hardware impairments in a multiple-antenna base station affects the uplink spectral efficiency (SE), with focus on Massive MIMO. This distortion is correlated across the antennas, but has been often approximated as uncorrelated to facilitate (tractable) SE analysis. To determine when this approximation is accurate, basic properties of distortion correlation are first uncovered. Then, we separately analyze the distortion correlation caused by third-order non-linearities and by quantization. Finally, we study the SE numerically and show that the distortion correlation can be safely neglected in Massive MIMO when there are sufficiently many users. Under i.i.d. Rayleigh fading and equal signal-to-noise ratios (SNRs), this occurs for more than five transmitting users. Other channel models and SNR variations have only minor impact on the accuracy. We also demonstrate the importance of taking the distortion characteristics into account in the receive combining.

Content of Code Package

The article contains 11 simulation figures, numbered 2-12. Figure X is generated by the Matlab script simulationFigureX.m for X=2,...,12. The package contains one Matlab function (functionRlocalscatteringApprox.m) and one data file (quantizationLevels.mat), which are used by some of the scripts.

See each file for further documentation.

Acknowledgements

This paper was supported by ELLIIT and CENIIT.

License and Referencing

This code package is licensed under the GPLv2 license. If you in any way use this code for research that results in publications, please cite our original article listed above.

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