Principal Component Compression Method for Covariance Matrices Used for Uncertainty Propagation

Uncertainty of communication signals measurement

“…A VSA software is being developed that uses the compressed covariance matrix [2] to propagate uncertainty trough the calculations such as error vector magnitude. More of the software will be presented in the CPEM 2014 conference.…”

“…In the compact covariance approach [2] the data is analyzed in the frequency domain. The results retained by the analysis are the covariance terms at each frequency and the dominant eigenvalues that describe the correlation across the frequencies.…”

“…This rearrangement does not affect the eigenvalue results. The complex baseband signal covers the frequency range from -f N to +f N, where f N is the Nyquist frequency and the compact covariance software [2] has been modified to accept this data format. In this example, the modulation response m(t) is measured using a Vector Signal Analyzer (VSA) with a 40 MHz bandwidth and a sampling rate of 128 MSa/s.…”

“…We outline the compressed covariance matrix algorithm for complex data. A detailed description of the compressed form covariance matrix for real waveform is presented elsewhere [2]. In wireless communications, the RF carrier is modulated with a complex modulation waveform m(t), such that…”

Characterization of High-Speed Balanced Photodetectors

“…DRTOs contain multiple analog-todigital converters and consequently this creates errors at subNyquist frequencies [13]. The effect of these can be reduced by calibration [14] but these corrections will increase the uncertainties at these frequencies [15]. Alternatively, selecting a comb repetition frequency that fulfills the criteria outlined in [13] will avoid the sub-Nyquist spurs and make the best use of the instrument ADC linearity.…”