Error vector magnitude (EVM) measurements can provide a great deal of insight into the performance of digital communications transmitters and receivers. With proper use, EVM and related measurements can pinpoint exactly the type of degradations present in a signal and can even help identify their sources.
Primarily a measure of signal quality, EVM provides both a simple, quantitative figure-of-merit for a digitally modulated signal and a far-reaching methodology for uncovering and attacking the underlying causes of signal impairments and distortion. EVM measurements are growing rapidly in acceptance, being already the required modulation quality measurement in such important technology standards as 3GPP W-CDMA and IEEE 802.11a/b/g WLAN, and they are poised to appear in several upcoming standards.
This application note from Keysight Technologies, Inc. provides useful tips that will assist in accurately making and understanding EVM measurements.
The error vector is the vector difference at a given time between the ideal reference signal and the measured signal. Expressed another way, it is the residual noise and distortion remaining after an ideal version of the signal has been stripped away. EVM is the root-mean-square (RMS) value of the error vector over time at the instants of the symbol (or chip) clock transitions.
Depending on the technology, EVM is reported as a percentage of the square root of the mean power of the ideal signal, as a percentage of the square root of the average symbol power, or as a percentage of the peak signal level, usually defined by the constellation’s corner states. The EVM value can also be reported in units of dB and some wireless networking standards use the term “relative constellation error” (RCE) instead of EVM.
While the error vector has a phase value associated with it, this angle generally turns out to be random, because it is a function of both the error itself (which may or may not be random) and the position of the data symbol on the constellation (which, for all practical purposes, is random). A more useful angle is measured between the actual and ideal phasors (I-Q error phase or phase error), which contains information useful in troubleshooting signal problems. Likewise, I-Q error magnitude, or magnitude error, shows the magnitude difference between the actual and ideal signals.
The magnitude of the error vector versus time measurement shows the error vector magnitude variations as a signal change over time—that is, at and between symbol decision timing points.
The spectrum of the error vector (or error vector spectrum) is the frequency spectrum of the error vector time.
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