Gaussian Noise Modeling is a statistical approach used to describe and analyze noise in various systems, particularly in communication and signal processing. In this model, noise is assumed to have a Gaussian (or normal) distribution, which means it follows the well-known bell curve characterized by its mean (average) and variance (spread or power). This type of noise is often referred to as “white noise” when it has a constant power spectral density across different frequencies.
We propose a method to estimate the input power dependency of the transceiver BER-OSNR characteristic. Experiments using commercial transceivers show that estimation error in Q-factor is less than 0.2 dB.
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