RE: Realise a bandwidth segmentizer

Hello Jeff Long,

Thank you for your answer.

I am really new to GNU Radio and DSP, so I am not sure to have understood what you said: do you suggest to get rid of the "stram to vector" blocks ?
I also do not know what a single pole IIR filter is, I will document myself and try to implement that solution once I got my head around the concept.

Anyway, thank you for your answer, have a nice day,

Alex

P. S.: could you give me possible pointers to good references to learn the concepts quicker ? I already
stumbled across the wonderful PySDR blog, and was wondering if there were other similar/complementary online ressources ?

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De : Discuss-gnuradio <discuss-gnuradio-bounces+alex-heu=hotmail.com@gnu.org> de la part de Jeff Long <willcode4@gmail.com>
Envoyé : mardi 15 mars 2022 15:43
À : discuss-gnuradio@gnu.org <discuss-gnuradio@gnu.org>
Objet : Re: Realise a bandwidth segmentizer

 

The Complex To Mag^2 block can operate on a vector, so that part you can get for free. If you don't actually need the mean, it could be sufficient to use a Single Pole IIR filter (also takes vectors) as a smoothing function.

On Tue, Mar 15, 2022 at 9:39 AM e heuchamps <alex-heu@hotmail.com> wrote:

Hello everyone,

I am trying to implement a bandwidth segmentizer (cutting a given bandwidth into smaller channels) and energy detector using GNU Radio, as schematically shown here below, but I am experiencing some trouble.

More precisely, to achieve the desired result, I have tried to implement two python blocks, given in the attached archive, in files "compute_average_power.py" and "custom_thres.py".
The goal of those blocks is to compute the average power contained in all the channels (compute_average_power.py), and feed that computed value to a self-made threshold block (custom_thres.py).
So far, the implementation does not work.

I have already learned in this post thanks to Markus Müller that using np.mean (where np is short for numpy) is bad because it depends on the length of input_items.

I have however not been able to reach the desired result. Can someone help me out ?

Thank you, have a nice day,

Alex


P. S. : the whole, complete, code is given in the attached archive, in the "bw_segmentizer.py" file.