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https://designers-guide.org/forum/YaBB.pl Design >> RF Design >> spur - prediction from time domain https://designers-guide.org/forum/YaBB.pl?num=1213354613 Message started by cmos_cowboy on Jun 13th, 2008, 3:56am |
Title: spur - prediction from time domain Post by cmos_cowboy on Jun 13th, 2008, 3:56am Hi, I am designing PLL divider and I am trying to estimate spur levels based of deterministic jitter. I have done some transient simulations with supply ripple and using veriloga code i can show the edge-to-edge period of the output. How do I convert this data to phase noise? thanks in advance, cc |
Title: Re: spur - prediction from time domain Post by Ryan Cheung on Jun 14th, 2008, 6:10am Hi, Do a fft on your transient waveform of Vc. Then convert the spectrum to VCO ouput by multiplying Kv/s. Then you will achieve the spur with the unit of dBc. |
Title: Re: spur - prediction from time domain Post by chenyan on Jun 14th, 2008, 7:57am Can you do a fft with time long enough? I think you can see the spur tones but maybe not accurate enough amplitude |
Title: Re: spur - prediction from time domain Post by cmos_cowboy on Jun 16th, 2008, 9:28am Just to clarify. It is a digital type divider. All I am interested in doing at the moment is trying to work out the divider phase noise not the full PLL. The divide values are large but the output is re-timed so I can reduce simulation time by reducing the divider value as only the front-end and sampler add jitter. Hence the ouput frequency is higher that it would be in reality. I can measure the edge-to-edge jitter of the ouput clock and plot it in the time domain. However if say any periodic ripple is added to the supply, at a frequency that is not harmonically related to the output clock then this modulate the ouput and cause a spur. I can take a pk-pk or rms of the Jee I record, this data is obviously periodic (at what will be the spur frequency) so only one period is required. I dont think it is correct to try and convert this to phase noise in the ususual way (PN=20log(Jee_in_rads)) as it is not a gaussian distribution. So how do I do it? |
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