An Experimental Procedure for Assessing EVM Performance of VNA-Based Measurement Systems

The accuracy of Error Vector Magnitude (EVM) measured at component level using a vector network analyzer (VNA) mainly depends on the dynamic range available for acquiring the relevant incident and reflected modulated waves. In this work, we propose a new experimental procedure for reproducing the same power levels that would be generated by the device-under-test (DUT), but without introducing the DUT's nonlinearity. This approach allows for accurately establishing the EVM profile measurable by a given VNA-based measurement system, thereby enabling the optimization of the available dynamic range for a given target DUT. The approach has been experimentally validated by measuring two nonlinear DUTs across two configurations of a V NA-based measurement system.

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Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1109/arftg65332.2025.11168141
Primary Topic
Library Science and Administration
Type
article
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article

An Experimental Procedure for Assessing EVM Performance of VNA-Based Measurement Systems

Library Science and Administration
article

An Experimental Procedure for Assessing EVM Performance of VNA-Based Measurement Systems

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Abstract

The accuracy of Error Vector Magnitude (EVM) measured at component level using a vector network analyzer (VNA) mainly depends on the dynamic range available for acquiring the relevant incident and reflected modulated waves. In this work, we propose a new experimental procedure for reproducing the same power levels that would be generated by the device-under-test (DUT), but without introducing the DUT's nonlinearity. This approach allows for accurately establishing the EVM profile measurable by a given VNA-based measurement system, thereby enabling the optimization of the available dynamic range for a given target DUT. The approach has been experimentally validated by measuring two nonlinear DUTs across two configurations of a V NA-based measurement system.

University of Bologna (IT)
Openalex Percentile: Top 35%
Library Science and Administration
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