## using eye diagram to model output waveform

Started by 6 years ago●3 replies●latest reply 6 years ago●91 viewsThank you

Yes I have the time domain data

I forgot to ask if you have the original data stream.

I'm assuming that your channel acts like

\[r = h\left(s\right) + n\]

where \(s\) is the transmitted signal, \(r\) is the received signal, \(h\) is a linear time invariant system, and \(n\) is white noise (this may work if \(n\) is colored noise, but I'd have to, like, think about that answer).

If you *do* have the original data stream, and if the SNR is high enough, then you should be able to use an ARMAX algorithm to come up with a model of the channel distortion (\(h\)), and then once you have that, come up with an estimate of \(n\) by subtracting a distorted but noise-free version of the signal from \(r\).

If you *don't* have the original data stream, but if you can reconstruct it somehow, then you can do the same thing -- but doing this sort of thing blind is harder.

I don't know if this is the usual way to do this -- if it isn't, hopefully someone will pipe up with something useful.