Signal and Power Integrity Tutorial: Measuring Clock Jitter Sensitivity to Power Rail Noise, Pt. 2

Figure 1. 400 mVpp oscillation on the power trace
is due to 48 MHz clock noise.

In Part 1, we used a function generator to create a power source with a known perturbation. Seeing that the noise on the power rail and the clock period were synchronous when we observed both traces together using a WavePro HD oscilloscope, we knew that there was a clear relationship between the two to be further investigated. Now, we're ready to examine more closely how the clock jitter responds to voltage variations on the power rail.

Signal and Power Integrity Tutorial: Measuring Clock Jitter Sensitivity to Power Rail Noise, Part 1

Figure 1. Voltage variations on the power rail
shown in the same grid as the clock period track
(jitter track). These waveforms are the basis of
the clock jitter sensitivity measurement. The
inverse relationship between the jitter track and
the power trace shows that the clock
is sensitive to variations in rail voltage.

In a previous post, we described A Robust Method for Measuring Clock Jitter with Oscilloscopes as variation in a clock signal’s period. Clock jitter is characterized by the standard deviation (sdev) of the clock period measurement. The track function of the clock period sdev shows us the variations in jitter over time, synchronous with the waveform source. 

In this post and the next, we’ll show how to make use of the clock period track function to match jitter variations to possible sources of jitter, in particular to voltage variations on the clock power rail. The offset voltage of a function generator powers a clock signal source. By creating a known variation in the function generator output, we can match that to the resulting clock jitter to calculate the clock jitter sensitivity to rail voltage changes. A known clock jitter sensitivity value can help you predict how a design will respond to rail voltage changes.

Oscilloscope Basics: When to Use Track to Graph Oscilloscope Measurements

Figure 1: Pulse Width Modulated waveform (yellow)
and Track math operator (blue),
where the X-axis scaling is identical for both.

Modern oscilloscopes contain many tools that can be used for analyzing data, including Track and Trend math functions. Both Tracks and Trends graphically display measurement results and locate anomalies. The main similarity between Tracks and Trends is that the Y-axis of both operators is the measurement parameter itself (for example, Pulse Width, Duty Cycle, Rise Time, Slew Rate, etc.). The main difference between the two math operators is their X-axis, in which the Track uses the identical X-axis and synchronous horizontal scaling as the input waveform, whereas the Trend uses units of chronology. A Track, in essence, is a waveform of the measurement values. A Trend is a data logger showing the history of change in measured parameter values, but points are not necessarily synchronous with the measured waveform.

Use Tracks for Anomaly Detection

The Track provides valuable debugging information by directly pointing to an area of interest. 

Notice the negative-going spike in the Track waveform in Figure 1. Figure 1 occurs at the point in time where the input waveform reaches its most narrow pulse width, and the Track instantly finds it, indicating when one measurement deviates from the others in the graph. The Track identifies the exact location in time where the narrowest or widest pulse width has occurred, and fully describes the measurement changes occurring throughout the entire waveform. Since oscilloscopes can acquire thousands or even millions of waveform edges within a single acquisition, the Track allows an engineer to quickly "find the needle in a haystack".

Signal and Power Integrity Tutorial: A Robust Method for Measuring Clock Jitter with Oscilloscopes

Figure 1. Clock jitter measured as a variation
of clock signal absolute period.

Clock jitter is the variation of a clock signal’s frequency or period. Either measurement carries the same information, but the period measurement is a simple time interval measurement easily performed using a real-time oscilloscope. If we have a robust way of measuring clock jitter, we have the basis for measuring the clock signal’s sensitivity to other features in the environment that can affect the period. Voltage noise on the power rail is just one external force that can affect clock jitter, which we'll show you how to measure in a future post.

In this post, we’ll demonstrate a robust method for measuring clock jitter using an example from Dr. Eric Bogatin’s webinar, “The Impact of Power Rail Noise on Clock Jitter.”  

The clock in our examples is a 5-stage ring oscillator which generates a square wave signal between 10 and 66 MHz. The test instrument is a WavePro HD 12-bit, 4-Ch, 8 GHz, 20 GS/s, 5 Gpts oscilloscope with 60 fs sample clock jitter.

In the process, we make a series of oscilloscope sample clock tests and timebase adjustments as  consistency checks. While measuring jitter is less about absolute accuracy than about the relative precision of measuring the time interval from cycle to cycle, a fundamental part of that is ensuring the absolute accuracy of the oscilloscope’s timebase.