EVS computes the instantaneous Error Vector Spectrum (EVS) between two signals. The measurement works with the Vector Signal Analyzer meter block (VSA) or the Vector Network Analyzer block (VNA). The EVS is the spectrum of the vector differences between the measured and source inputs to the VSA meter.
|Block Diagram||System Diagram||N/A|
|VNA/VSA||System VNA meter, System VSA meter||N/A|
|Time Span||Real value||Varies|
|Time Span Units||List of options||N/A|
|Number Averages||Integer value||>0|
* indicates a secondary parameter
Note: If the selected system diagram is configured for a swept simulation, the measurement will have additional parameters for specifying the plotting configuration for each swept parameter. These parameters are dynamic and change based upon which data source is selected. See Section 1.3.3 for details.
The measurement returns complex values in units of voltage. The voltage can be displayed in dB by selecting the dB check box in the Add/Modify Measurement dialog box. The x-axis for this measurement is in frequency units. The range of the frequency axis is fc-fs/2≤f≤fc+fs/2, where fc is the center frequency of the measured signal and fs is the sampling frequency.
Right-clicking the cursor on the measurement when it is displayed on a rectangular graph will display the settings used to compute the result at the selected data point.
The instantaneous error vector spectrum is computed based on the following:
where V[fk] is the amplitude of the fk frequency, fs is the sampling frequency of the measured signal, and N is the number of FFT bins. Ei is the sequence of error vectors and wi is an optional windowing function. For wi=1, i=0,1,...,N-1 (no windowing), the spectrum equation is the discrete Fourier transform.
The error vectors are computed as:
E[k] = Meas[k] - Src[k]
where Meas and Src are the two complex signal inputs to the VSA meter block.
The number of FFT bins is determined by the Time Span and Units settings, and is set to the equivalent number of samples in the data window.
The spectrum may optionally be computed from an average of several spectrum computations. This occurs when the number of averages is set to a value other than 1. When averaging is in effect, individual spectrums are computed by computing spectrums for several windows of input data, each offset by 50% from the previous data window. A Taylor window function is applied to the data before each FFT is performed. The average of all the spectrums is then used to compute the spectrum values.