I've just one question :
How can I write a model like y = x + w,( with w a white gaussian noise) with a fixed SNR and a noise variance equal to 1. What coefficient may I have before x ?
Thanks !
Answer
If you define the SNR as the ratio of the signal power and the noise power in dB, you have
SNRdB=10log(PsPw)
where Ps is the power of the desired signal and Pw is the noise poiwer. If the noise w has a mean of zero, then Pw=σ2w=1. From (1) (with Pw=1) you get the desired value of Ps for a given value of SNRdB:
Ps=10SNRdB/10
In order to normalize the signal x such that it has the desired power Ps you first need to know its power Px. Dividing x by √Px will give you a unity power signal, which can then be multiplied by √Ps in order to obtain the desired SNR:
s=√Psx√Px=10SNRdB/20x√Px
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