Beating the jitter bug – how to apply multiple measurement strategies to identify noise source: Page 2 of 5

November 03, 2016 // By Andrea Dodini, Keysight Technologies
Digitising an analogue signal can improve the chances that the information it represents arrives at its destination uncorrupted by electrical noise. However, digital signals can be corrupted if noise signals alter their timing enough to push the transitions in the bitstream out of sync with the sampling point. This ‘jitter’ means the bitstream is misinterpreted, and can be a particular problem at very high data rates.

Looking jitter in the eye

How do you know how bad your jitter problems are? An eye diagram can help, superimposing all the bit periods of a captured waveform, as in Figure 1.

Figure 1: An idealised eye diagram (Source: Keysight Technologies).

This eye diagram has smooth transitions at the left and right crossing points forming a large, wide-open ‘eye’ in the centre. At point X, the waveform should have settled and so can be sampled with the least chance of a bit error. Figure 2 shows a more realistic eye diagram, which reveals a lot about the signal.

Figure 2: An irregular eye diagram offers a wealth of information (Source: Keysight Technologies).

Let’s list them:

  • The amplitude of the bottom of the waveform varies less than that at the top, so the signal seems to carry more 0s than 1s;
  • There are four different trajectories in the bottom, so at least four 0s in a row are possible;
  • There are only two trajectories at the top of the waveform, so it carries a maximum of two 1s in a row;
  • The waveform has two different rising and falling edges, showing that it is subject to deterministic jitter;
  • The rising edges have more spread than the falling edges, and some of the crossover points intersect below the threshold level, showing that duty cycles are being distorted causing 0s to have a longer On time than 1s.
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