| 摘要 |
In optical transmission networks, the data signals are degraded by transmission components which are present in said networks. According to the invention, a histogram of the statistical signal distribution is first created from a data signal that has been degraded by Gaussian noise and for example, interference noise. The histogram resembles a Gaussian distribution (2, 3) provided that the other signal noises, for example interference noise do not amount to a multiple of the Gaussian noise (1). Said histogram (2) is then compared with a Gaussian distribution. As the strength of the Gaussian noise, which corresponds to the variance of the Gaussian distribution, is unknown, this comparison is repeated in sequence for a large number of Gaussian distributions with different variances. If the selected variance of the Gaussian distribution matches the Gaussian noise present in the data signal, the statistical signal distribution of the other parasitic signals can be recognised by development, that is by the numerical subtraction of this Gaussian distribution from the histogram of the degraded data signal and can be identified. This method determines the quality of a data signal very rapidly and reliably. Conclusions concerning the possible sources of noise can be drawn from the identification of the parasitic signals.
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