Finding Sources of Jitter with Real-Time Jitter Analysis

Introduction

As data rates increase effects of jitter becomes critical and jitter budgets get tighter. Instruments such as real-time oscilloscopes and Bit Error Ratio Testers (BERT) are optimized for determining the total amount of jitter and worst-case eye-opening in your high-speed digital system and can be used to test for compliance based on industry standards. In addition, some real-time instruments can separate random and deterministic jitter components to predict/extrapolate worst-case total jitter (TJ) and eye-opening based on a user-specified Bit Error Ratio (BER), typically 10-12. But when jitter measurements do not meet a particular minimum standard, or if jitter measurement results are “too close for comfort,” then measuring the amount of component or system jitter is just half of the jitter test equation. Determining the root cause of jitter is the other half of the test equation. The focus of this paper will be to address some practical “tips & tricks” on using real-time oscilloscopes with jitter analysis and high-speed pulse/pattern generators to separate and time-correlated specific deterministic jitter components to help identify, measure, and view sources of systematic timing errors.

Table of Contents:

•  
• Understanding Jitter
• Real-Time Jitter Analysis
• Typical Characteristics of Individual Jitter Components
• Isolating Jitter Components in the Real World
• Isolating and Measuring Duty Cycle Distortion (DCD)
• Isolating and Measuring ISI
• Isolating Uncorrelated Periodic Jitter (PJ)
• Isolating Random Jitter (RJ)
• Analyzing a Spread Spectrum Clock
• Conclusions

Understanding Jitter

Jitter is the deviation of a timing event of a signal from its ideal position. The traditional way to measure jitter is with an eye diagram using repetitive acquisitions on an oscilloscope as shown in Figure 1. Looking at this composite view, you might assume that you have a band of worst-case jitter equal to the width of the rising and falling edges of the eye diagram. You might also assume that all edges of your signal are jittering about to the same degree. Both of these assumptions would be incorrect. Jitter is complex and is composed of both random and deterministic jitter components. Random Jitter (RJ) is theoretically unbounded and Gaussian in distribution. “Unbounded” simply means that if you wait long enough, the peak-to-peak jitter will increase indefinitely theoretically.

This means that an eye diagram may never show the worst-case condition. If the jitter in your system consisted of just random jitter, then each edge of the data signal would have the same probability of timing error. 

Deterministic Jitter (DJ) is bounded and doesn’t follow any predictable distribution. It consists of several different sub-components and is usually caused by a systematic problem in your high-speed digital design. For this reason, DJ is sometimes referred to as systematic jitter. If you were to view each individual edge of the data signal, you would probably see that particular data edges contribute different amounts of timing error. Depending on the data pattern, some edges in the serial pattern will always be shifted to the right (positive timing error), while other edges will always be shifted to the left (negative timing error) relative to their ideal timing locations. And then the random jitter component would cause these individual data bit edges to randomly bounce around the shifted/offset deterministic amplitude of the jitter.

Using an eye diagram, you can sometimes quickly determine if your system is dominated by random or deterministic jitter, or possibly a combination of the two. Using the oscilloscope’s variable intensity or color-graded display capability, you can visually look for the existence of “bright” trace paths within the infinite-persistence display. Referring to the traces in Figure-1, we can see several well-defined paths of brightness. This is a clear indication of deterministic jitter. Some of the data edges consistently occur in some locations while other edges occur in other locations of the eye diagram. The power of a real-time scope is the ability to view these particular data edges individually as we will see later in this paper.

Another technique to determine the existence of random versus deterministic jitter is to use the scope’s histogram feature. By taking a look at a slice of data across the center of the screen, we can see in Figure 1 that the distribution of edge placements is a combination of random and deterministic jitter. If the Probability Distribution Function (PDF) were Gaussian (the classic bell-shaped curve), then the system jitter would probably be dominated by random jitter. The fact that this particular PDF is approximately bi-modal in distribution is another indication of the existence of a significant amount of deterministic jitter