On Tue, Sep 6, 2011 at 2:25 PM, Ryan P. [email protected] wrote:
In one application, we have 25K channels which are then resampled using
but our first goal is to do it with one filterbank, if possible.
9600 bps signal in a 25 ksps channel, you can switch to using the
To be clear I’m not looking for arbitrary channel size channelizer, when I
said 25K/50K etc, I was just referring to the fact that we are using
channelizers of various sizes.
This was related to not wanting to resample after every channel, not the
different channel bandwidth.
the gr_pfb_clock_resampler looks like exactly what I need. Will give it
a
shot.
Great! It’s worked great for me in the past. Interested to hear other’s
results, though.
Also, in our case where we are actively using 20% of channels from the
channelizer, it is more advantagous to provide the filterbank with the least
computationally intensive channel filter and add a more selective filter on
only the channels we are using (but do so with N separate filter blocks), or
is the filterbank implementation efficient enough to worry about it and we
should design the channel filter to best fit the ultimate need?
For N channels, every N taps added to the prototype filter adds only 1
more
tap per channel, so it shouldn’t be too much overhead to provide a
better
filter in the channelizer. Now, the channelizer implementation uses
time-domain FIR filters internally, so if you are asking to use hundreds
of
more taps, than it might be more computationally efficient to use
external
FFT filters for the channels you need. But I doubt it, honestly. There’s
going to be some crossover somewhere that you might just have to
experiment
with to find out.
The other thing is that the PFB clock resampler is another filter. In
the
dbpsk2 and dqpsk2 demodulators that are currently in the master branch,
I
implemented the RRC filter for this, so it becomes the matched filter,
too.
You can use other filters for this stage, so you might think about how
to
pair this filtering stage with the channelizer filtering stage for the
best
computational and signal performance (choose the best point on the
Pareto
front, if you will).
Tom