Beating the jitter bug – how to apply multiple measurement strategies to identify noise source: Page 3 of 5

November 03, 2016 //By Andrea Dodini, Keysight Technologies
Beating the jitter bug – how to apply multiple measurement strategies to identify noise source
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.

Other ways to think about jitter

There are other ways of visualising jitter, and applying several of them to a signal can help identify the sources of jitter.

The histogram
A histogram plots the range of values exhibited by a parameter along the x-axis versus the frequency of its occurrence on the y-axis. In jitter analysis, histograms can plot waveform parameters such as rise time, fall time, period, or duty cycle, to reveal conditions that can be correlated with circuit conditions.

The histogram in Figure 3 shows period jitter in a clock signal. The double peak at right suggests that the signal includes second and fourth harmonics.

Figure 3: Histogram of period jitter (Source: Keysight Technologies).

The bathtub plot
The bathtub plot in Figure 4 graphs the bit error rate (BER) of a signal versus its sampling point. The horizontal scale represents the time it takes for one symbol to be transmitted. BER is represented on a vertical log scale.

Figure 4: Bathtub plot (Source: Keysight Technologies).

When the sampling point is at or near the transition points (0 and TB), the BER is 0.5 meaning it is equally likely that a bit will or will not be transmitted successfully. The curve is fairly flat in these regions, dominated by deterministic jitter. As the sampling point shifts away from the transition point, the BER drops off rapidly as the jitter becomes dominated by random processes. The bathtub plot shows that, as in Figure 1, the best time to sample the signal is halfway between its symbol’s transitions.

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