The following call is how I read data into MATLAB from the GNURadio file sink. I think this would almost work in Octave as well but I haven't tried. If not it, it at least illustrates the proper format.
FileID = fopen('Filename','r'); import_channels = 2; SamplesPerFrame = 1024; import_format = 'float32'; x = fread(FileID,[import_channels SamplesPerFrame],import_format)'; complex_baseband = complex(x(:,1),x(:,2)); I have this embedded in a MATLAB system class. I extricated the fopen/fread() calls for clarity. HTH -- Martin K. On Thu, Jun 7, 2018 at 9:30 AM, Federico 'Larroca' La Rocca < flarr...@gmail.com> wrote: > Hello again, > > To export from GNU Radio to octave, you should first use a "File Sink" > block and then one of the scripts in gr-utils/octave. I'm pretty sure they > are compatible with matlab too. > > About the SNR, that depends on what you want. If you want the power of > noise that actually affects your decision system divided by the power of > the symbols, then MER is what you are looking for (assuming your sampling > and frequency correction works properly). If you want the more classic SNR > (i.e. power of the useful signal divided by the total noise power in the > band), then that's more involved. You may try the following: since you know > the constellation points and the pulse, you may easily calculate the power > of the useful signal (assuming your AGC works properly and that the channel > is flat fading). The difference between this power and the actual received > power is due to noise (assuming independence). > > However, what matters performance-wise is the amount of noise that gets > into the decision system, and not the actual SNR. > > Hope it helps! > > >
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