We are all aware that a noise signal is added to a signal as it is transmitted from transmitter to receiver, especially when using a wireless channel. Although we can't entirely eliminate such noise signals. With a better understanding of noise, its pattern, etc., we may be able to recover the original transmitted data.
For a typical wireless communication process,
y = x + n
where x and y are the transmitted and received signals, respectively, and n stands for noise.
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We can see that the standard deviation and mean of the gaussian noise represent the entirety of the noise pattern in the abovementioned PDF of the gaussian random variable. These two variables are crucial for almost all noise types.
The sample values' standard deviation indicates how they vary from one another. It offers us a general sense of the range in which the signal parameter falls (for example, the amplitude of the signal). The image above is a PDF and not the actual gaussian noise signal. The mean value of gaussian noise may therefore be confusing to many of you. This is how a signal with gaussian noise appears.
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The mean value may be zero because of this.
MATLAB Script
Output
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