Timeline for Symbol Timing recovery for modulation producing ISI
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
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| Dec 8, 2020 at 0:42 | vote | accept | FourierFlux | ||
| Nov 17, 2018 at 17:38 | comment | added | Andy Walls | The timing error signal might temporarily leave that region due to noise or ISI, and that's why one filters the error signal. Chasing the unfiltered error signal sample by sample will lead to a very jittery symbol clock estimate and poor clock tracking stability; which is precisely why one doesn't use a PID filter with only a proportional term, for this task. The output of the integral branch of the filter provides an estimate of the average symbol clock period. An nonlinear implementation detail is that the integral branch is constrained to stay within$\pm x\%$ of the expected clock period | |
| Nov 17, 2018 at 6:30 | comment | added | FourierFlux | Ok so we're implicitly accepting the error will never actually settle but bounce around and hope it stays in an acceptable region. I still don't see why it would stay in this region though depending on the sequence of symbols sent. Also why have an integral term in the loop instead of a simpler scaler? | |
| Nov 17, 2018 at 0:18 | comment | added | Andy Walls | A better question might be to pick a particular TED, say Garnder, and investigate what happens to its S-curve under various input conditions? As TED gain goes down, the magnitude of error estimates goes down and locking a timing loop takes longer. If you get the S-curve to totally collapse, the error estimates will be junk. | |
| Nov 16, 2018 at 23:46 | history | edited | Andy Walls | CC BY-SA 4.0 |
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| Nov 16, 2018 at 23:45 | comment | added | Andy Walls | These slides touch briefly on some of the concepts: gnuradio.org/wp-content/uploads/2017/12/… . In operation of the loop, the timing error estimate may never be 0, but it may continually bounce above and below 0 when the loop is locked and tracking. | |
| Nov 16, 2018 at 23:35 | comment | added | Andy Walls | The TED, like Gardner or Muller & Muller, is not the "algorithm". The TED is part of the algorithm, for PLL based timing recovery. The TED emits an error signal that is an estimate of the timing error. This error signal is filtered to drive a correction of the symbol clock which is then fed back for generation of the next error estimate from the TED. A properly tuned loop will continually minimize the error in the estimated symbol clock timing. That mimized error and the PLL tuning do depend on the TED gain which in turn, does depend on the noise and ISI on the input. | |
| Nov 16, 2018 at 23:24 | comment | added | FourierFlux | Why does it work at all though? If you look at a Raised Cosine modulated signal it's very non-symmetric around the sampling times, algorithms like Muller and Gardner seek a position that is symmetric about the sampling time or use zero crossings which in this case don't align with the symbol timing. | |
| Nov 16, 2018 at 23:02 | history | answered | Andy Walls | CC BY-SA 4.0 |