How to simulate the outage probability of user data rate versus signal to noise ratio?
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I have 4 users, and I want to simulate the outage probability which is the probability of the user data rate is less than the predefined threshold value i.e. if the threshold rate per user is = 0.512.
After changing the signal to noise ratio SNR from -20 dB to 30 dB, I obtain the rate matrix with dimensions (number of users × the length of SNR vector), where each element in this matrix represents the rate of certain user at specific SNR value as follows:
SNR_vector_dB=-20:10:30; %the SNR vector
R_th = 0.512; % the user data rate threshold value
% Rate matrix with dimensions (number of users =4 * the length of SNR vector=6)
R = [0.0021 0.0191 0.1466 0.7368 1.5617 1.9838; ...
0.0021 0.0191 0.1466 0.7368 1.5617 1.9838; ...
0.0041 0.0370 0.3190 0.9267 1.6591 2.1856; ...
0.0041 0.0370 0.3190 0.9267 1.6591 2.1856];
Can anyone help me in simulating the outage probability versus SNR?
2 Comments
Rik
on 1 Apr 2020
I'm not sure what the goal is exactly. It looks like you need to do something like this:
Pout=mean(R<R_th,1);
Accepted Answer
Rik
on 1 Apr 2020
Since that apparently was the solution, I'll post it as an answer:
SNR_vector_dB=-20:10:30; %the SNR vector
R_th = 0.512; % the user data rate threshold value
% Rate matrix with dimensions (number of users =4 * the length of SNR vector=6)
R = [0.0021 0.0191 0.1466 0.7368 1.5617 1.9838; ...
0.0021 0.0191 0.1466 0.7368 1.5617 1.9838; ...
0.0041 0.0370 0.3190 0.9267 1.6591 2.1856; ...
0.0041 0.0370 0.3190 0.9267 1.6591 2.1856];
Pout=mean(R<R_th,1);
plot(SNR_vector_dB,Pout)
ylabel('estimated outage probability')
xlabel('SNR (dB)')
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