[ibis-macro] Re: concern on Rx_Noise
- From: <fangyi_rao@xxxxxxxxxxx>
- To: <vladimir_dmitriev-zdorov@xxxxxxxxxx>, <ibis-macro@xxxxxxxxxxxxx>
- Date: Tue, 21 May 2013 09:57:25 -0600
Thanks for the comment, Vladimir. Basically Rx_Noise^2 is the integral of PSD
over the entire bandwidth, so it is an incomplete description of noise
characteristics.
To correct an error in the example in my original email, the noise RMS after
the averaging filter is Rx_Noise/sqrt(N), not (1/N)*Rx_Noise/sqrt(N).
Fangyi
From: Dmitriev-Zdorov, Vladimir [mailto:vladimir_dmitriev-zdorov@xxxxxxxxxx]
Sent: Monday, May 20, 2013 6:30 PM
To: RAO,FANGYI (A-USA,ex1); ibis-macro@xxxxxxxxxxxxx
Subject: RE: concern on Rx_Noise
Fangyi,
Yes, we can study noise propagation only if we know its spectral density.
Noise PDF (or sigma for Gaussian case) can serve only as rough characterization
of the noise generated on the spot, but not the one that propagates through the
channel (or filter).
What's the difference compared to Tx_jitter specifying 'Gaussian'? In this
case, we don't know spectral density either and typically assume uncorrelated
noise.
Vladimir
________________________________
From: ibis-macro-bounce@xxxxxxxxxxxxx<mailto:ibis-macro-bounce@xxxxxxxxxxxxx>
[ibis-macro-bounce@xxxxxxxxxxxxx] on behalf of
fangyi_rao@xxxxxxxxxxx<mailto:fangyi_rao@xxxxxxxxxxx> [fangyi_rao@xxxxxxxxxxx]
Sent: Monday, May 20, 2013 6:02 PM
To: ibis-macro@xxxxxxxxxxxxx<mailto:ibis-macro@xxxxxxxxxxxxx>
Subject: [ibis-macro] concern on Rx_Noise
Experts;
While thinking about how to handle Rx_Noise in redriver, I came to realized
that Rx_Noise's behavior in the downstream channel can't be defined. As
described in BIRD 123, Rx_Noise is the RMS of a Gaussian voltage noise, and its
unit is Volt. That information is inadequate to determine how the noise is
transferred when passing through a filter because to compute the filtered noise
one needs to know the input noise Power Spectral Density (PSD) in
Volt/sqrt(Hz), but not RMS.
Take a simple example and consider a low pass filter that performs a time
average on the signal within a window of 1UI. Assume N time points are used per
UI. It's well known that the RMS of the average over N random noise samples is
(1/N) * Rx_Noise / sqrt(N)
where 1/N is the weight of each sample interval. Now the filter output noise
depends ambiguously on the number of time points per UI, which is a simulation
setting.
Am I missing something?
Fangyi
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