sheldon
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hslsc311,
You should probably start from the other way around, what are you interested in learning from the FFT. 1) Do you want to know the THD of the design? 2) Do you want to know how oversampling effects the quantization noise floor?
The answer to 1 & 2 effects the number of tones in the signal band and ultimately the number of bins in the FFT. Next, you need to understand that you will be using windowing, the cosine^2 window most likely. So you will to allocate additional bins because windowing will spread the signal across multiple FFT bins.
In case of #1 above, assume that you would like to see the first five harmonics, fundamental + 4 harmonics. Then you will need 2 FFT bins for dc 2 FFT bins for the fundamental 2 FFT bins for each harmonic or you would like 12 FFT bins in the signal band. Then you would like to oversample the signal band by 64 times. Since the math works out best when the FFT is a power of two, you will 16*64 FFT bins (points) or 1024 points in the FFT.
For case #2 If you look in Appendix C of Schreier, he talks about the need to have a large ratio of noise to signal when calculating SNR. As I remember his recommendation is 10x more noise bins. So instead of 12 FFT points in the signal band, you will need 120 points. Rounding up to 128 FFT points, the total number of FFT points is 128*64 points or 8,192 points.
NOTE: Case #2 only covers the effect of quantization noise. If you really want to consider the effect of device noise, that is, run a transient noise analysis, then you will need to run a power spectral density analysis and it will require even more points in the FFT.
Hope this helps,
Sheldon
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