Hi Kartik,
I heartily agree with you, you need a lot of random variables, but the question is: in which shape?
Do you need the noise source to produce more different types of amplitude distributions? Do you need those in the channel models?
"Blocks for hypothesis testing" sounds pretty interesting. Can you flesh out that idea a little more? In my head, I'm not sure what a hypothesis is here.
Best regards,
Marcus
Till now, based on my experience in communication systems, I saw extensive need of probability and random variables.
So, now, if we are considering GNU Radio to be a full-fledged communication systems simulator, I think we can have wrappers of statistical analysis functions of Scipy. We can have GRC blocks for the same.
So, for an example, for spectrum sensing applications, instead of writing a code with Scipy library, we can have some blocks for direct hypothesis testing.
Regards,Kartik Patel
On Thu, Jan 26, 2017 4:07 PM, Martin Braun martin.braun@ettus.com wrote:
On 01/26/2017 12:07 AM, Kartik Patel wrote:
> Hi,
>
> I am not sure how relevant is this, but it's worth a consideration.
>
> Can we have a probability and statistical toolbox? It may include
> various probabilistic distributions, their random number generators,
> their PDFs and CDFs. These are very much useful in a communication
> system analysis. (Example: middleton noise etc. for simulations). Even
> adding various statistical functions like hypothesis testing,
> regressions, distribution fitting etc. can be added.
Sure, although scipy has pretty good ones already. Can you elaborate on
how this would be useful for GNU Radio specifically?
-- M
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