The error power ratio estimates EVM for a wide class of impairments: Monte Carlo simulations

Karl Freiberger; Harald Enzinger; Christian Vogel

doi:10.1109/INMMIC.2017.7927308

The error power ratio estimates EVM for a wide class of impairments: Monte Carlo simulations

Karl Freiberger, Harald Enzinger, Christian Vogel

Institute of Signal Processing and Speech Communication (4420)

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

The error vector magnitude (EVM) is an important system level metric for RF and mixed-signal communication systems and related building blocks. Recently, we have introduced the error power ratio (EPR), a method based on the noise power ratio for estimating the EVM, and presented selected simulation and measurement results. The present paper compares EVM and EPR for many different systems by randomly varying impairment model parameters. To model a multitude of nonlinearities with memory using few parameters, we use a novel baseband Wiener-Hammerstein model with feedback. In 3000 trials of combined phase noise, IQ mismatch and nonlinearity, the mean error (EPR minus EVM) is less than -0.25 dB. Outliers are within -0.5 and -0.8 dB over the entire range of EVM levels (-80 to -15 dB).

Original language	English
Title of host publication	Proceedings of the 2017 International Workshop on Integrated Nonlinear Microwave and Millimetre-Wave Circuits, INMMiC 2017
Publisher	Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781509058624
DOIs	https://doi.org/10.1109/INMMIC.2017.7927308
Publication status	Published - 11 May 2017
Event	2017 International Workshop on Integrated Nonlinear Microwave and Millimetre-Wave Circuits, INMMiC 2017 - Technische Universität Graz, Graz, Austria Duration: 20 Apr 2017 → 21 Apr 2017 Conference number: 35116 http://www.inmmic.org/

Conference

Conference	2017 International Workshop on Integrated Nonlinear Microwave and Millimetre-Wave Circuits, INMMiC 2017
Abbreviated title	INMMiC
Country/Territory	Austria
City	Graz
Period	20/04/17 → 21/04/17
Internet address	http://www.inmmic.org/

ASJC Scopus subject areas

Electrical and Electronic Engineering
Modelling and Simulation
Computer Networks and Communications

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10.1109/INMMIC.2017.7927308

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Freiberger, K., Enzinger, H., & Vogel, C. (2017). The error power ratio estimates EVM for a wide class of impairments: Monte Carlo simulations. In Proceedings of the 2017 International Workshop on Integrated Nonlinear Microwave and Millimetre-Wave Circuits, INMMiC 2017 Article 7927308 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/INMMIC.2017.7927308

The error power ratio estimates EVM for a wide class of impairments: Monte Carlo simulations. / Freiberger, Karl; Enzinger, Harald; Vogel, Christian.
Proceedings of the 2017 International Workshop on Integrated Nonlinear Microwave and Millimetre-Wave Circuits, INMMiC 2017. Institute of Electrical and Electronics Engineers, 2017. 7927308.

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Freiberger, K, Enzinger, H & Vogel, C 2017, The error power ratio estimates EVM for a wide class of impairments: Monte Carlo simulations. in Proceedings of the 2017 International Workshop on Integrated Nonlinear Microwave and Millimetre-Wave Circuits, INMMiC 2017., 7927308, Institute of Electrical and Electronics Engineers, 2017 International Workshop on Integrated Nonlinear Microwave and Millimetre-Wave Circuits, INMMiC 2017, Graz, Austria, 20/04/17. https://doi.org/10.1109/INMMIC.2017.7927308

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title = "The error power ratio estimates EVM for a wide class of impairments: Monte Carlo simulations",

abstract = "The error vector magnitude (EVM) is an important system level metric for RF and mixed-signal communication systems and related building blocks. Recently, we have introduced the error power ratio (EPR), a method based on the noise power ratio for estimating the EVM, and presented selected simulation and measurement results. The present paper compares EVM and EPR for many different systems by randomly varying impairment model parameters. To model a multitude of nonlinearities with memory using few parameters, we use a novel baseband Wiener-Hammerstein model with feedback. In 3000 trials of combined phase noise, IQ mismatch and nonlinearity, the mean error (EPR minus EVM) is less than -0.25 dB. Outliers are within -0.5 and -0.8 dB over the entire range of EVM levels (-80 to -15 dB).",

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The error power ratio estimates EVM for a wide class of impairments: Monte Carlo simulations

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