TMob wrote:
>
> Hi,
>
> I am currently trying to use the USRP to sense the 802.11 channels for
> activity. So far, I am using the usrp_spectrum_sense to do this. Each time
> I get the callback from gr.bin_statistics_f, I calculate the signal power
> in the returned data vector using the following formula:
>
> for bin in m.data:
> signalPower +=
> 20*math.log10(math.sqrt(bin)/tb.fft_size)-20*math.log10(tb.fft_size)-10*math.log(tb.power/tb.fft_size/tb.fft_size)
> signalPower /= tb.fft_size
>
> According to previous posts, this should give me the signal power at the
> given center frequency in dBm.
> Unfortunately, it turned out that the values that I get using this code,
> vary very much, e.g. with the FFT size and the gain. When I leave gain and
> FFT size per default I get values from -28 through +5 (dBm) which
> definitely does not correspond to dBm. Is there any mistake in the
> formula? Is this really dBm that I get?
>
> Because the usrp_fft.py example shows more realistic values (around -50 -
> -60dBm) than the usrp_spectrum_sense.py, I was wondering if somebody could
> explain how usrp_fft gets to these values. All I can see in the source
> code there is that a USRP source is defined and connected to the scope.
> But where is the conversion into dBm done? Can this be applied to
> usrp_spectrum_sense somehow?
>
> Thanks,
>
> TMob
>
did anyone have the answer to this question? is it because of the
usrp_fft.py have the windowing block? regarding the windowing block, do any
body know why the blackmanharis is chosen?
Adib
-----
Mohd Adib Sarijari
Universiti Teknologi Malaysia
www.fke.utm.my
www.utm.my
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