Hi,
I've found (thanks to Firas) the solution to the incorrect localization in frequency of the maximum values. It's due to the factors tune-delay and dwell-delay of the bin_statistics_f function. You have to increase these values (setting both in 50e-3 I can locate quiet well the max values) cause the results vary depending on the hardware and the PC performance. Now I will try to calibrate my system to measure the received power, but it's a different issue. Hope it can help other people. Best Regards. killoqg wrote: > > Hi, > > I'm having the same problem: the output of my spectrum analyzer and the > output of the spectrum_sense.py doesn't match. I'm trying to detect > activity int the GSM900 band, but it's impossible with the outputs I > obtain. > > I was trying to correct the code and I think that your formula is > incorrect. I'll try to explain: > > P=E/N, with P=power of signal, E=energy of signal and N=number of points > > 1) The output of the c2mag (gr.complex_to_mag_squared) is the energy of > the signal, so the power of the same signal will be these values divided > by N (number of points), I think the square root is not necessary. > > 2) For the same reason, when you make > 10*math.log(tb.power/tb.fft_size/tb.fft_size) I think it should be > 10*math.log(tb.power/tb.fft_size) > > 3) After that, the last operation (signalPower /= tb.fft_size) is > unnecessary, it's already done in 1) > > The incorrect range of values could be a problem of the ref-scale > parameter. I tried to correct the output values using > -20*math.log10(tb.ref_scale) but they're still out of range. > > In my case, either the maximum values of the output doesn't match with > the ones in the spectrum analyzer view. > > Does anybody have an answer to this problem? It seems that the > spectrum_sense is used in several projects, but how does it function? > > Thanks in advance. > > > adib_sairi wrote: >> >> >> >> 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 >> >> > > -- View this message in context: http://old.nabble.com/usrp_spectrum_sense-vs.-usrp_fft-tp21708925p28946269.html Sent from the GnuRadio mailing list archive at Nabble.com. _______________________________________________ Discuss-gnuradio mailing list Discuss-gnuradio@gnu.org http://lists.gnu.org/mailman/listinfo/discuss-gnuradio
