What is Self-noise in TED algorithm

Started by AiDrmek 3 weeks ago1 replylatest reply 3 weeks ago93 views

I am working on a research project. The main task is timing error correction algorithm. I start with studying algorithms which are exist. Currently I have read about Gardner TED algorithm for PSK modulation signals. In the last publication (“A Modified Gardner Detector for Symbol Timing Recovery of M-PSK Signals” or “Symbol-Timing Recovery with Modified Gardner Detectors”) was mentioned a self-noise of TED algorithm. It is written that because of PSK signals are highly bandlimited, the self-noise is appeared.

  • One drawback of the Gardner detector is that it has significant pattern-dependent jitter or self-noise for bandlimited signals.
  • the jitter floor caused by self noise, as it is typical for symbol timing recovery in general,is lowered by nearly two orders of magnitude.

Honestly, I have never read about self-noise in contest of TED algorithm. Why does self-noise appear? Is it the same self-noise as it appears in microphone?

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Reply by fharrisJune 4, 2021


Self noise is the random transitions between states that can be seen in the eye diagram when you are offset in time from where the eye is maximally open. I have a paper that compares self noise of different timing recovery algorithms... it was too big to upload so I copied the back end of the paper and converted it to a pdf.

the original paper appeared in WPMC-2018 and is likely on line IEEEexplore

Comparing Statistics of Maximum Likelihood, Gardner, and Band Edge Filter Timing Recovery

  Part of Timing Error Detectors.pdf