the photocurrent is not Gaussian SO that the LMS algorithm is not the theoretically optimum solution. Other algorithms have been proposed, suitable for the coefficient determination in the presence of non-Gaussian noise that are more complex than LMS, but LMS seems to perform better especially in conditions of high dispersion and the presence of PMD [74]. As a matter of fact, while chromatic dispersion is in principle a deterministic phenomenon and presents only very slow changes due to aging and temperature fluctuations, PMD is a random fluctuating phenomenon. For this reason using an optimum algorithm for the equalizer coefficient identification is much more critical in the presence of a sizeable PMD. Moreover, it is also demonstrated that, when using an electronic dispersion compensator based on the FFE-DFE the availability of an automatic threshold control (ATC) algorithm is very beneficial for the overall system working. As a matter of fact the compensator, while equalizing the intersymbol interference, also filters the noise with a digital filter that is generally adapted for equalization and not for noise filtering (Figure 5.55). Since the equalizer implements a feedback structure the statistical distribution of the noise is changed after the equalizer, and more adaptive the equalizer, the more the noise distribution is filtered differently at different moments. An example of noise distributions is shown in Figure 5.56, where the decision-variable distribution estimate is shown in cor- respondence to the transmission of a "1" and the transmission of a "0." Besides the distri- bution in the absence of equalizers, the distributions for different equalizers are shown. Telecommunication Networks FIGURE 5.55 Block scheme of an FFE-DFE electronic dispersion compensator. Without equalization Equalization FFE9-DFE1 + LMS Equalization FFE9-DFE2 + LMF Equalization FFE9-DFE4 + LM8 FIGURE 5.56 Effect of the electronic equalization at the receiver with an FFE-DFE on the decision sample probability distri- bution. (Afte