Error vector magnitude to SNR conversion for nondata-aided receivers

Error vector magnitude (EVM) is one of the widely accepted figure of merits used to evaluate the quality of communication systems. In the literature, EVM has been related to signal-to-noise ratio (SNR) for data-aided receivers, where preamble sequences or pilots are used to measure the EVM, or under...

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Bibliographic Details
Published in:IEEE transactions on wireless communications 2009-05, Vol.8 (5), p.2694-2704
Main Authors: Arslan, H., Mahmoud, H.A.
Format: Article
Language:English
Subjects:
Amplitude modulation
Applied sciences
AWGN
Bit error rate
blind receivers
Channels
Codes
Communication standards
Communication systems
Devices
Error vector magnitude (EVM)
Errors
Exact sciences and technology
Fading
Information, signal and communications theory
IQ imbalance
Mathematical analysis
Modulation, demodulation
Phase noise
pulse amplitude modulation (PAM)
Pulse modulation
Quadrature amplitude modulation
quadrature amplitude modulation (QAM)
Rayleigh fading
Receivers
Signal and communications theory
Signal to noise ratio
signal-to-noise ratio (SNR)
SNR estimation
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Testing
Transmission and modulation (techniques and equipments)
Vectors (mathematics)
Wireless communication
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Summary:Error vector magnitude (EVM) is one of the widely accepted figure of merits used to evaluate the quality of communication systems. In the literature, EVM has been related to signal-to-noise ratio (SNR) for data-aided receivers, where preamble sequences or pilots are used to measure the EVM, or under the assumption of high SNR values. In this paper, this relation is examined for nondata-aided receivers and is shown to perform poorly, especially for low SNR values or high modulation orders. The EVM for nondata-aided receivers is then evaluated and its value is related to the SNR for quadrature amplitude modulation (QAM) and pulse amplitude modulation (PAM) signals over additive white Gaussian noise (AWGN) channels and Rayleigh fading channels, and for systems with IQ imbalances. The results show that derived equations can be used to reliably estimate SNR values using EVM measurements that are made based on detected data symbols. Thus, presented work can be quite useful for measurement devices such as vector signal analyzers (VSA), where EVM measurements are readily available.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2009.080862