But if you do a single 1024-FFT, you'd only operate on 1024 of the input
samples!
And: the FFT doesn't just give you power values, but complex values;
mathematically, the FFT is a DFT, and the DFT is an invertible linear
operator $\mathcal F$:
$\mathcal F: \mathbb C^{N} \mapsto \mathbb C^{N}$
which maps complex vectors to complex vectors of size $N,\quad
0<N\in\mathbb N$. It is, in fact, representable as square matrix with
column (and row) vectors being samples of the orthogonal complex
sinusoids $e^{j\frac{2\pi}N nk},\, k=0,\ldots,N-1$; that is, it can also
be understood as a /base change matrix/, that just represents the "input
vector" according to a different base, orthogonal base.
In the physical sense: the input vector base was represented by the
standard basis $\mathbf e_N$, meaning that each base vector represents a
single point in time – the sample time of the respective entry; the
"output" of the transform is represented on a base of orthogonal
frequencies. This is an invertible operation – really just another way
to look at *the same signal*. I think this is really important to keep
in mind:
The Fourier transforms are /not/ magical by any means. What they do is
represent *the same signal* from a different point of view. It can be
/interpreted/ as transform between time and frequency domain (or space
and impulse, or...). The DFT is still just a boring, old, square,
orthogonal, invertible matrix that produces output of the same
dimensionality as it takes input.
As you can see, the DFT/FFT itself never reduces the amount of data.
What you might be referring to is some kind PSD estimate done by first
|·|² a lot of DFTed vectors and then averaging them. The data reduction
here lies in the magnitude square operation and the average, not in the DFT.
The point here is that you're throwing away a whole lot of information,
and I'm not convinced that's what Hasini needs!
Best regards,
Marcus
On 12.01.2017 05:54, Mallesham Dasari wrote:
> Hi Marcus,
>
> Raw IQ samples take lots of memory because each sample will be around
> 8Bytes. Suppose, if we 1Msps sample rate, just for 10 minutes of data,
> we get 10*60*1M*8B = 4.8GB data. On the other hand, if you store just
> FFT with 1024 bin, we get 4.8GB/1024 power values right (which has
> very less size)?
>
> Please correct me if I am wrong.
>
> Thanks
>
> On Wed, Jan 11, 2017 at 7:32 AM, Marcus Müller
> <[email protected] <mailto:[email protected]>> wrote:
>
> Hi Mallesham,
>
> I don't understand – the raw IQ samples and their FFT have the
> same size, and data type.
>
> Maybe you've understood something that I (and Martin) didn't –
> could you elaborate?
>
> Best regards,
> Marcus
>
>
> On 01/11/2017 12:56 AM, Mallesham Dasari wrote:
>> Hi Hasini,
>>
>> If you are trying to print just the FFT, it should not be an
>> issue. If you print raw iq samples, then you will run out of
>> memory. By long, you mean how long? Days?
>>
>> On Tue, Jan 10, 2017 at 3:16 PM, Martin Braun
>> <[email protected] <mailto:[email protected]>> wrote:
>>
>> Hasini,
>>
>> can you please re-state what you're trying to do? That might
>> help you
>> getting some answers. It is not quite clear from this email.
>>
>> Cheers,
>> Martin
>>
>> On 01/02/2017 09:16 PM, Hasini Abeywickrama wrote:
>> > Hi all,
>> >
>> > I have a flowgraph that reads a signal and writes its FFT
>> samples to a
>> > file. I need to run this continuously (for a long time),
>> without running
>> > out of memory.
>> >
>> > I tired deleting the earlier FFT samples from the file but
>> that messes
>> > up with reading the data. I also tried starting writing to
>> a different
>> > file after some time so the initial file can be completely
>> deleted. But
>> > it did not work as well.
>> >
>> > What would be the best approach for this? Any thought would
>> be very much
>> > appreciated.
>> >
>> > Regards,
>> > Hasini
>> >
>> >
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>> >
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>>
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>>
>>
>> --
>> Best Regards,
>> *Mallesham Dasari*
>> Department of Computer Science
>> Stony Brook University
>> USA - 11794
>>
>>
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> _______________________________________________ Discuss-gnuradio
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> Best Regards,
> *Mallesham Dasari*
> Department of Computer Science
> Stony Brook University
> USA - 11794
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