Agilent Measurement Journal - Issue 5 - 2008 - (Page 36)

Understanding bathtub curves BERTSCAN is a technique ﬁrst formalized by the ANSI for Fibre Channel and later adopted into the T11.2 Jitter standard. 2, 3 It deﬁnes a method for estimating total jitter by measuring the BER. The T11.2 document, treated as a reference standard for many datacom standards, models the timing error using a PDF. This timing error gives rise to BER, when the bits are sampled at instants away from the ideal sampling point, as illustrated in Figure 4. From a qualitative perspective, the BER measured with the ideal sampling point yields the best possible value. The value worsens as the sampling point is moved across the eye in either direction, towards the eye crossing points (e.g., the left crossing point or the right crossing point in Figure 4). If the BER is plotted as a function of sampling time (or sampling delay offset), the resulting plot resembles a bathtub. The minimum BER occurs at the optimum sample point, which is usually near the center of the eye. The maximum BER occurs at the left and right crossing points. Figure 5 depicts a typical bathtub plot for the case of large levels of random jitter. The total jitter is deﬁned as the difference between the eye opening at 10-12 BER and the bit period. In practice, generating this plot requires measurement of BER levels to very low probabilities. As this is a very time-consuming process, the usual practice is to measure only a part of the bathtub curve, usually down to a BER of 10-9, and extrapolate to the required levels (e.g., 10-12). The extrapolation process assumes certain models and the accuracy depends on the validity of these assumptions and models. For example, the T11.2 document suggests that the RJ(x) in Equation 4 can be modeled as a Gaussian process. This enables the extrapolation of lower BER values from the data collected at higher BER levels. Sampling point, t= 0 .5 x TB Left edge Right edge Left crossover point Right crossover point 1 unit interval, TB Figure 4. Eye diagram showing the effect of sampling on the measured BER 36 Agilent Measurement Journal

Table of Contents Feed for the Digital Edition of Agilent Measurement Journal - Issue 5 - 2008

Agilent Measurement Journal Issue 5 Finding a New Path when Assumptions Break Down Contents Testing MIPI D-PHY Protocols Oscilloscope Firmware Update DNA Replication Joining the LTE/SAE Trial Initiative Testing Proteins Praise for DC Power Analyzer Scripting Features for AMDS Testing Hybrid PCBA Systems Improving the Gene Expression System Workflow Turning a “Good Enough” Test Strategy into One That’s Reliable, Repeatable and Traceable Understanding the Effects of Limited-Bandwidth Channels on Digital Data Signals Introducing the 3GPP LTE Downlink Validating the 26 Validating the Physical and Protocol Layers in DDR Memory Interfaces Understanding Total Jitter Measurements of Low Probabilities Using Behavioral-Model Simulation to Accurately Predict First-Order PLL Performance Creating Synchronous High-Frequency Sampling across Multiple Digitizers Overcoming the Challenges of Testing FlexRay Networks Understanding Operating Life and Repeatability of Electromechanical Switches and their Effect on Total Cost of Ownership Implementing Micro and Nano LC/MS Techniques for High Sensitivity Lipidomics Analysis

Agilent Measurement Journal - Issue 5 - 2008

For optimal viewing of this digital publication, please enable JavaScript and then refresh the page. If you would like to try to load the digital publication without using Flash Player detection, please click here.