[ibis-macro] Re: Query on AMI BIRD

  • From: Mike Steinberger <msteinb@xxxxxxxxxx>
  • To: Huang chunxing <huangchunxing@xxxxxxxxxx>
  • Date: Wed, 25 Jul 2007 08:28:20 -0500

Huang-

Regarding equalization optimization, it is true that if you have enough time and/or compute resources, you can do just about anything in SPICE, including equalization optimization. The real question, as you suggest, is the amount of time required to get the job done. With our AMI models, we're simulating of the order of one million bits per minute. My experience to date has been that that's fast enough to gain insight by iterating through many solutions. I invite you to consider how long it would take to simulate a million bits in SPICE; and please be assured that, as personnel from both IBM and TI have pointed out, a million bits is required.

As regards jitter simulation, part of the question is whether one is concerned with the bulk of the jitter, such as perhaps two to three sigma from the mean, or whether one is concerned with rarer events, such as perhaps seven sigma from the mean (and therefore corresponding to a probability of 1e-12). While time domain simulations may be sufficient for offsets of two to three sigma, they are impractical for offsets of seven sigma. Furthermore, I suggest that attempting to extrapolate from three sigma to seven sigma is not going to yield reliable results. There are other methods, however, that will yield more reliable results for low probability events.

I suggest that we've come to a point where we have an adequate mutual understanding, and that further discussion should wait until we have specific results to discuss. In that regard, if you have data you could share with the committee that would help us understand what methods are already yielding satisfactory results for an acceptable level of effort, that would be very useful.

Thanks.
Mike Steinberger

Huang chunxing wrote:
Hi Mike and Kumar,

Thank you for your both answers.
Global optimization is really difficult, or may be impossible. Here is one of 
the AMI model target,
The proposed modeling solution must:

-       Support automatic optimization of device settings based on simulation

I agree that AMI model could support optimization. But, in my opinion, AMI model didn't give much extra advantages on automatic equalization optimization over Spice encrypted model as I expected. If AMI model is fast enough for equalization parameter sweep, this maybe one practical way to do optimization work. Jitter simulation techniques is another problem. Different jitter may have different suitable simulation way. As for DCD jitter, I prefer to the way to modulate DCD on data waveform and simulate it bit-by-bit. Other methods based on approximate algorithmic model may be not so accurate.
Regards,
Huang

Huawei Technologies Co.,Ltd.
Tel:     86 755 28976229
FAX:     86 755 28976758
Email: huangchunxing@xxxxxxxxxx
Web:   http://www.huawei.com

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in error, please destroy any and all copies of this message including attached files in your possession. ----- Original Message ----- From: "C. Kumar" <ckumar@xxxxxxxxxxx>
To: <huangchunxing@xxxxxxxxxx>
Cc: "IBIS-ATM" <ibis-macro@xxxxxxxxxxxxx>
Sent: Monday, July 23, 2007 4:16 PM
Subject: RE: [ibis-macro] Re: Query on AMI BIRD



huang:

1. A global optimization probably does not exist. It is even difficult
to tell with certainty whether it is better to have equalization at both
ends,   Tx and Rx. For example in some cases you may find that it is
better to have all the equalization done at the Rx end (adaptive dfe ,
for example), turning on the optimization at the Tx end may even lead to
poorer solution.
It is best to do a solution space analysis. The present ATM standard
should enable you do such solution space evaluation

2. DCD can be applied by the EDA vendor at the TX end and will be
reflected in the wave form passed through the GetWave function at the
RX.
3. Another item for you to notice is the standard per se does nor
require you to generate the wave form by the impulse response. in other
words the GetWave function is not concerned about where the input wave
form comes from. For example if you have a circuit level Tx model , in
principle, it is possible to generate the wave form in circuit space and
pass the waveform to the RX GetWave. In fact a good(probably at some
point a must)  sanity test is to verify the algorithm model generated
waveform against circuit simulation generated waveform. -----Original Message-----
From: ibis-macro-bounce@xxxxxxxxxxxxx
[mailto:ibis-macro-bounce@xxxxxxxxxxxxx] On Behalf Of Huang chunxing
Sent: Friday, July 20, 2007 10:46 PM
To: Mike Steinberger
Cc: IBIS-ATM
Subject: [ibis-macro] Re: Query on AMI BIRD

Mike,

Thanks for your detailed answer. You really help me know some clues to
solve the problems, but I still have some unclear points listed below.

1) What's peaking filter? It is continous time filter composed of zeros
and poles?
    I think the optimal coefficients calculation for non-adaptive
equalization is tough task. In my opinion, the impulse response is most
suitable for determining equalization tap and coefficients range. When
we only consider the transmitter equalization, it may use impulse
reponse to calculate optimal coefficients. In order to dsitinguish
receiver equalization, I would like to call transmitter equalization
emphasis. But when receiver have equalization either, like DFE or CTE, I
am not sure the coefficient determined by impulse response will be best.
Because the optimal coefficient is only calculated by emphasis itself
and doesn't consider the equalization case, like type, coefficients tap
and range. I think it will be different from that optimal coefficient
calcuated by the method considering emphasis and equalization together.
Like two cases below, I think optimal coefficients of case a is
different from that of case b.
a)emphasis---link---receiver without equalization
b)emphasis--link---receiver with equalization

My knowledge of equalization is very limited , maybe I omitted some
optimal coefficients method which could solve my case, or my talk is
just nonsense. : )

2) I know DCD caused by transmitter is different from that caused by
receiver and DCD caused by receiver is most contributed by refernece
voltage shift. Here I mainly care about DCD caused by transmitter. Only
the DCD caused by transmitter do transfer through channel and will be
amplified. Whether the method DCD imposed on the data signal or method
which DCD imposed internal to the transmitter model you suggested, I
think it should be implemented in non-LTI mode in order to modulate the
DCD jitter on data signal. In other words, DCD should be implemented in
GetWave() function and simulator will do the bit_by_bit simulation. Did
I get the right point?
Thanks again. Have a nice day!

Regards,
Huang

Huawei Technologies Co.,Ltd.
Tel:     86 755 28976229
FAX:     86 755 28976758
Email: huangchunxing@xxxxxxxxxx
Web:   http://www.huawei.com

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----- Original Message -----
From: "Mike Steinberger" <msteinb@xxxxxxxxxx>
To: <huangchunxing@xxxxxxxxxx>
Cc: "IBIS-ATM" <ibis-macro@xxxxxxxxxxxxx>
Sent: Wednesday, July 18, 2007 10:12 PM
Subject: Re: [ibis-macro] Query on AMI BIRD


Huang-

Thank you for your questions. We very much appreciate your interest in

this standard.

I have inserted some responses below. Please let me know if I have failed to address your concerns.

Mike Steinberger
SiSoft

Huang chunxing wrote:
Hi Experts,

I have some difficult in understanding  the AMI BIRD.
1) Most equalization of RX and TX is non-adaptive. Chip vendors
don't have any adaptation codes to embed into DLL function and the DLL
function won't have the ability to calculate the optimal equalization
coefficients. Then who will be in charge of calculating the optimal
equalization coefficients, users or simulators? Is it possible for
simulator to do this kind of work?
You are partially correct in that some of the equalization in the current designs is not adaptive; however, you're not entirely correct
in
that some of the equalization in the current designs is adaptive. In general, transmit equalization is not adaptive while receive equalization (either decision feedback equalization (DFE) or peaking filter) usually is. Thus, a receiver model truly is responsible for optimizing the receive equalization, and is in fact the only entity in

the simulation which can perform this function, since the receive optimization algorithms tend to be highly proprietary.

For (non-adaptive) transmit equalization, the situation is more
complex.
In most real systems, the transmit equalization settings must be determined by experiment during system integration; and it is quite
true
that the transmitters themselves are not able to perform this optimization on their own. In simulation, however, there are
algorithms
which can determine the optimum transmitter equalization settings
given
the impulse response of the channel and the configuration of the equalizer (e.g., number of taps, tap spacing, available tap weights). The difference between real world and simulation is that in the real world, the impulse response of the channel is not available to the transmitter.

In the simulation, a number of optimization algorithms are possible.
All
of them require the impulse response of the channel and the configuration of the equalizer(s); however, the optimization criterion

can vary quite a bit, and so the algorithm to optimize to the chosen criterion can vary as well. Thus, while the optimization algorithm for

the transmitter truly is a separate function, it is a function which offers vendors another opportunity to differentiate their offering. Since the DLL is some packaging that will already be in place, it is also a convenient place to put this other function. Please note that this does not necessarily prevent the EDA platform from also implementing some form of optimization, although to do so, the EDA platform must somehow get a description of the equalizer
configuration.
2)If the channel is LTS, all simulation will be done by impulse
response mode. How to consider the jitter effects, especially DCD.
According to PNA(Phase Noise Amplifier) and experiment, DCD will be
amplified by the low-pass channel. Direct statistical processing without
DCD amplification won't be accurate.
After discussing this point at some length, we concluded that the LTI assumption is not sufficient for all modeling needs. Thus, while the Init() function and its associated processing depends on the LTI assumption, the GetWave() function implements a time domain simulation

which only assumes that the passive electrical interconnect is LTI. Thus, the GetWave function is free to model nonlinear and time varying

behaviors of the pin electronics.

As regards DCD in particular, there are two entirely satisfactory ways

to model the effects of this impairment using models which are
compliant
with this standard:
1. The DCD can be imposed on the data signal that is input into the transmitter model. In order to do this, the data signal must have
finite
rise and fall times, preferably greater than the DCD to be imposed; however, that is entirely consistent with the real world that is being

modeled. Every data generator has a finite rise and fall time.
2. The DCD can be imposed internal to the transmitter model. This is probably more appropriate and more accurate since in the real world
the
DCD will be caused by circuit effects internal to the transmitter. Similarly, a real receiver can introduce DCD as well, and that DCD
will
have a different effect than DCD at the transmitter. It may therefore
be
appropriate for receiver models to implement DCD as well.
The problem may do not belong to AMI  category and maybe I missed
something here. I hope some experts could help clarify it. Thanks in
advance.
Regards,
Huang

Huawei Technologies Co.,Ltd.
Tel:     86 755 28976229
FAX:     86 755 28976758
Email: huangchunxing@xxxxxxxxxx
Web:   http://www.huawei.com

Warning:  The information contained in electronic mail message is
intended
   only for the personal and confidential use of the designated
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   above. It may be privileged and confidential. If you have
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