I am working on a research work on transmitting ECG signals compressed by Compressed sensing over wireless body area network . The signal is affected by noise and small scale fading. The normalized mean square error is used to estimate the quality of the reconstructed signal at the receiver. When I run the same m file in matlab several times, I obtain different values for the mean square error, although the same channel signal to noise ratio is used. I think this is reasonable, do you agree? If so, how can I obtain a signal value to represent the quality of the reconstructed signal at the receiver?
You need to average the normalized MSE over several hundred of runs. It should converge to a value. You can repeat the experiment for different values of SNR.
First of all, make sure that the program has no errors. Check the quality of signal recovery in the absence of noise. Then count with strictly repetitive noise. Next, fix the power of the noise that it was strictly constant. And then, follow the tips Mobien Mohammed and Bo Lee. Best regards.
Thanks a lot for your help.
But running the file several hundreds of times consumes too much time, could you please tell me how can I perform this?
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