PJ and BUJ Results

Meas. mode:
Jitter
Waveform type:
NRZ
PAM4
NRZ Jitter Table
PAM Eye Table

The Jitter mode, Periodic Jitter (PJ) and Bounded Uncorrelated Jitter (BUJ) measurements are one component of Deterministic Jitter (DJ). In the results table, the following measurements are listed:

  • PJ (rms) and PJ (δ - δ), or
  • BUJ (rms) and BUJ (δ - δ)

Whether PJ or BUJ is reported depends on the Separation Method setting in the Advanced tab of the Jitter Mode Measurements Setup dialog. The Separation Method setting (either Spectral or Tail Fit) determines the method used to decompose RJ and RN.

PJ is a measure of the jitter that is uncorrelated to the pattern, yet is periodic. Jitter caused by a switching power supply near a clock is an example of periodic jitter. PJ (rms) is useful in the case where the PJ is of a known distribution. For example, a stress test may be developed in which sinusoidal PJ is intentionally injected. Assuming the injected PJ is the only PJ present, the system can be calibrated using the PJ (rms) measurement. Dual-Dirac PJ (δ - δ) is useful when the distribution is unknown. The dual-Dirac number allows various PJ measurements to be compared with one another, even when the distributions are dissimilar. It is a measure of how much the PJ affects the low-probability statistics of the uncorrelated jitter.

BUJ includes PJ, but it also includes other bounded uncorrelated effects that don’t cause clear peaks in the jitter spectrum. One common source with these characteristics is cross talk from adjacent traces on printed circuit boards or coupling within the chips themselves. The Spectral method of jitter separation will see cross talk as noise in the jitter spectrum, so it will only separate the PJ peaks and attribute the other effects to RJ. The Tail Fit method uses the low probability tails of the uncorrelated jitter histogram to measure in a region that BUJ does not contribute. This method is less accurate due to the use of a significantly fewer samples, but it allows for the separation of RJ from BUJ.

The δ-δ measurement algorithm is:

  1. An uncorrelated jitter histogram is constructed using edge models.
  2. Random Jitter (RJ) is measured.
  3. Using the measured value of RJ, a dual-Dirac model is fit to the histogram to obtain the PJ or BUJ measurement. The model is fit at a probability of 10-3 when using the Spectral separation method or an adjustable probability based on number of acquired samples when using Tail Fit.

PJ or BUJ (δ - δ) = UJ(prob) – 2 * Q(prob) * RJrms

The RMS measurement algorithm is:

  1. An uncorrelated jitter histogram is constructed using edge models.
  2. Random Jitter (RJ) is measured.
  3. The variance of the histogram is calculated.
  4. PJ or BUJ (rms) is calculated as follows:

PJrms or BUJrms = sqrt(Total Variance – RJrms2)

More Information

SCPI Commands

:MEASure:JITTer:PJ (PJ δ - δ, BUJ δ - δ)

:MEASure:JITTer:PJRMs (PJ rms, BUJ rms)