Difference between Eye Diagram and Bathtub Curve or plot | Eye Diagram Vs Bathtub Curve

This page compares Eye Diagram vs Bathtub Curve and mentions difference between Eye Diagram and Bathtub Curve or bathtub plot.

Both eye diagram and bathtub curves are used for signal integrity analysis.

Eye Diagram

eye diagram

Eye diagram is obtained using oscilloscope. Figure-1 depicts eye diagram of data. It is being generated when digital data is sampled and applied to the vertical input of CRO and data rate is applied as trigger for the horizontal sweep. Different modulation types will have different eye diagrams.

Eye diagram consists of multiple traces of data bits which are triggered by bit clock. Traces are superimposed which shows envelope of amplitude and timing fluctuations. In other words, eye diagram show range of amplitude and timing deviations associated with data bits.

Following measurements can be interpreted using eye diagram.
➨"Eye opening" indicates additive noise in the signal.
➨"Eye Width" indicates timing synchronization and jitter effects
➨"Eye overshoot/undershoot" indicates peak distortion due to interruptions in the signal path.
Refer Constellation Diagram vs Eye Diagram>>.

Hence eye diagram with large opening indicates data stream with little amplitude and timing noise. Eye diagram with small opening indicates data is very noisy.

Bathtub curve | Bathtub plot

Bathtub curve or bathtub plot

Bathtub curves are created with BERT (Bit Error Ratio Tester). BERT generates data which is passed through DUT. It measures transmitted data and compares for errors to determine BER (Bit Error Ratio). Here measurement location is swept across unit interval (UI) and based on this BER plot as function of UI is constructed. This plot resembles similar to cross section of bathtub and hence the name of plot is referred as bathtub curve or bathtub plot. Figure-2 depicts bathtub curve or bathtub plot of data. It is found from jitter PDF (thick line) and TailFit extrapolation (thin line).

Once jitter PDF is available, TailFit is applied in order to find corresponding bathtub curve. Bathtub range is dimensionless number i.e. BER. BER is probability of bit errors. The bathtub curve of timing errors is integral or CDF (Cumulative Density Function) of jitter PDF.

TailFit can predict probability of extremely rare bit errors. Bathtub plot for BER as low as 10-16 can be found easily. This method takes few seconds for measurement and analysis. To plot bathtub curve down to 10-12 BER using BERT requires many hours typically.

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