Normalizing Path Loss Model to Test Data
3 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
Looking for advice on methods of normalizing data. I have collected network level data and calculated the signal loss ('LOSS' in code below, measured in dB). I would like to compare this data to the free space path loss propagation model, as calculated in the code. To do this, I have tried to normalise the data between 0 and 1, however I am not getting the results I expected when I do this.
% Distance and path loss from test data
DIST = data.DIST;
LOSS = data.LOSS;
% distance vector
d = DIST;
% frequency
f = 1800e6;
% Calculate free space path loss model
FreeSpaceLoss = 20*log10(((4*pi*d*f)/3e8).^2);
% Normalise model
freeSpaceNorm = abs(FreeSpaceLoss)./max(abs(FreeSpaceLoss));
% Normalise test data
dataNorm = abs(LOSS)./max(abs(LOSS));
% Plotting data over normalised models
figure, hold on
plot(DIST, freeSpaceNorm, 'LineWidth',1.5)
plot(DIST, dataNorm, '.', 'MarkerSize', 7)
xlabel('Distance (m)')
ylabel('Loss (dB)')
title('PL Models vs Data')
legend('fspl', 'test data')
hold off;
I get the resulting plot, but the path loss model does not start at zero. I may be missing something small, or misunderstanding why this is happening - just looking for any suggestions on the best way to compare the two datasets.
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/569649/image.png)
Thanks in Advance.
3 comentarios
Mathieu NOE
el 6 de Abr. de 2021
hello
whatever the units or the scaling , it has to be coherent between measurements and theory...
now remember to remove zero valued data if you intend to use log scaling
Respuestas (0)
Ver también
Categorías
Más información sobre Inputs en Help Center y File Exchange.
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!