title: MATLAB: : Mean square error vs SNR plot
body: <p>I am having difficulty in understanding the logic behind generating a plot of SNR (db) vs MSE. Different Signal to Noise Ratio (SNR) is created by varying the noise power . The formula of MSE is averaged over <code>T</code> independent runs.</p>
  
  <p>For each <code>SNR</code>, I generate <code>NEval = 10 time series</code>. How do I correctly plot a graph of SNR vs MSE when SNR is in the range = [0:5:50]? Below is the pseudo code.</p>
  
  <pre><code> N = 100; %Number_data_points
  NEval = 10; %Number_of_different_Signals
  Snr = [0:5:50];
  T = 1000; %Number of independent runs
  
  MSE = [1];
  for I = 1:T
   for snr = 1: length(Snr)
     for expt = 1:NEval
      %generate signal
        w0=0.001;  phi=rand(1);
      signal = sin(2*pi*[1:N]*w0+phi); 
      % add zero mean Gaussian noise
      noisy_signal = awgn(signal,Snr(snr),'measured');
      % Call Estimation algorithm
      %Calculate error
      end
    end
  end
  
  plot(Snr,MSE); %Where and how do I calculate this MSE
  </code></pre>