(caveat - 13 years since I worked on this)
This is a real single-sample update Sliding DFT, not a block-based
method. The sample comes in, and used to perform a complex rotation to
each bin, followed by the frequency-domain convolution. There are no
twiddle factors as such. So the rectangular window is at best implicit -
I'm not sure it even has any meaning in this situation. The approach
from the outset was for the goal of real-time processing - i.e.
potentially for hours non-stop. We found (in the Cleaspeed project) that
single-precision floats would not support that; I don't know whether
anything less than double precision is required - those were the only
choices available.
It's "embarrassingly parallel" as an algorithm, so very suited to
dedicated massively parallel hardware. I know FPGAs are pretty powerful
these days so might well do the job (but some transformations are pretty
cpu-intensive too!). The Bath Uni team said they were using a
"mid-range" graphic card (on a Linux workstation).
Richard Dobson
On 19/03/2020 17:45, Eric Brombaugh wrote:
Wow - interesting discussion.
I've implemented a real-time SDFT on an FPGA for use in carrier
acquisition of communications signals. It was surprisingly easy to do
and didn't require particularly massive resources, although FPGAs
naturally facilitate a degree of low-level parallelism that you can't
easily achieve in CPU-based systems.
Based on this it might be feasible to build the SPV on a modest FPGA
rather than resorting to GPUs or specialized parallel CPU systems. The
main stumbling block that I see was your use of double-precision
floating point. If that level of accuracy is really necessary then a
higher end FPGA would be needed as most mid-range devices are geared
more for fixed point or single-precision floating point.
I was a bit confused by the ICMC paper when it came to windowing. The
SDFT structure I'm used to seeing (as discussed in the Lyons/Jacobsen
article you referenced) involves a rectangular window applied prior to
the twiddle calculations using a comb-filter structure. Is this window
replaced by your frequency domain convolutions, or are the cosine-based
windows applied in addition to the rectangular one?
Eric
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