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RMS to Peak-to-Peak Jitter Calculator

The amount of random jitter present in a signal may be quantified as either (1) the standard deviation of its Gaussian distribution (that is, an RMS random jitter value in ps), or (2) the peak-to-peak random jitter (in ps) at a specific bit-error ratio (BER). This calculator converts between these two quantities. That is, it converts RMS random jitter into peak-to-peak random jitter for a given BER. This calculator may also be used simply to calculate the crest factor (N) for use with the Jitter Budget Calculator (just enter "1" in Step 3).

Note that this calculator applies to time-interval error (TIE) jitter whose histogram (PDF) is 100% randomly distributed (that is, there are no deterministic components of jitter). It also assumes random components of jitter may be accurately modeled as a Gaussian distribution (generally a good assumption). Enter numbers below using integers or scientific notation (for example, enter 123 as 123, 1.23e2, or 1.23E2).

Step 1:  Enter desired BER Gaussian Jitter BER Statistics Table
Step 2:  Enter data-transition density (DTD, see below)
  This calculator solves for N using the equation,  
  BER Equation  
  N =  
  RMS PP Jitter Histogram
Step 3:  Enter Jitter in ps RMS
Step 4:   
Answer: Jitter (ps PP) = N x Jitter (ps RMS) =

What is DTD?

A signal's data-transition density (DTD) is the number of its edge transitions (rising and falling) divided by the total number of bits. For example, the DTD of the 10-bit pattern below is 6 transitions divided by 10 bits, or 60% (DTD=0.6).

Definition of Element and Node.

To avoid baseline wander, the same number of zeros and ones are transmitted on average. Such DC-balanced data is ensured by choosing an appropriate encoding scheme. This encoding also ensures a sufficient regularity of transitions in the encoded data pattern for downstream PLLs to acquire and maintain lock, enabling clock recovery at the receiver.

Many encoding methods specified by serial-data standards (such as 8B/10B encoding) and standard PRBS patterns produce 50% DTD on average. Therefore, DTD=0.5 is generally a good assumption. An obvious exception would be an 1010 (repeating) clock-like data pattern, for which DTD=1.

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