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Simulating with IBIS-AMI Models
By this point in the process, the SerDes component suppliers should have provided any missing IBIS-AMI models, which should be updated in your simulation testbench if they exist and are available. Now the focus shifts to post-layout verification. While it seems that we should be able to simply push the “simulate” button now with all the final models in place, there are often still things to consider with regards to IBIS-AMI models.
As discussed earlier, the algorithmic, or “AMI” section of the IBIS-AMI model represents the equalization functionality of the SerDes. At double-digit data rates, SerDes equalization techniques almost always employ real-time adaptation. To model this, AMI models will often have multiple settings available to the user, so that the equalization can be manually adjusted to best drive their specific channel. To figure out the best combination of settings, it is often left as “an exercise for the reader”, where the SI engineer has to sweep through the multiple combinations and figure out what works best.
With more advanced AMI models, the model itself will incorporate some or all of the adaptation into the channel simulation, closely emulating the behavior of the actual hardware. But even with these types of adaptive models, there are often settings to still review and optimize. For example, consider the following case, which uses a receiver AMI model that incorporates a continuous time linear equalizer (CTLE), automatic gain control (AGC, sometimes referred to as a variable gain amp, or VGA), and decision feedback equalization (DFE).
Figure 9 – Receiver equalization
In this particular model, each sub-module (CTLE, AGC, and DFE) adapts their settings dynamically, so you may expect that no manual intervention is needed. Running with the default settings, the following is observed.
Figure 10 – Initial channel simulation results
While the eye has an opening, the plots of the CTLE, AGC, and DFE coefficients are showing that they do not really converge during the simulation, and continue to bounce around. The initial settings had the AGC module adapting twice as fast as the CTLE module. Speeding up the AGC adaptation to 4x the CTLE adaptation speed yields these results.
With the quicker AGC adaptation, you can see that the coefficients for all three modules (CTLE, AGC, DFE) settle out and start to converge. But the convergence happens after about 150,000 bits of traffic are passed. So increasing the value of the “Ignore_Bits” parameter in the receiver’s AMI model from 40,000 to 150,000 will remove the first part of the simulation from the results, so the analysis tool evaluates the converged result, as would occur with the real hardware. This produces the result below.
Figure 11 – Converged receiver equalization settings
Just by adjusting some of the interdependent AMI adaptation model parameters, the eye height in this particular case was improved from 40mV to 85mV at the target BER of 1e-12, an improvement of over 100%.
Figure 12 – Result with converged receiver equalization settings
This illustrates some of the subtleties associated with simulating with advanced AMI models. The user still needs to carefully review the documentation supplied by the model provider, understand the adjustable settings available to them, and leverage them accordingly.
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Ken Willis is a Product Engineering Architect focusing on SI solutions at Cadence Design Systems. He has nearly 30 years of experience in the modeling, analysis, design, and fabrication of high-speed digital circuits. Prior to Cadence, Ken held engineering, technical marketing, and management positions with the Tyco Printed Circuit Group, Compaq Computers, Sirocco Systems, Sycamore Networks, and Sigrity.
More about Signal Integrity:
How to Address the Challenges of Serial Link Design and Analysis
Why SerDes Signaling Is Trending Towards PAM Encoded Signals
How to Build an IBIS-AMI Model (Video)