the cyclic algorithms try to minimize. It is nat- urally, a cost-related target, and in particular, it coincides with the CAPEX cost of the network. Even the model adopted in the last section talking about ILP linear optimization can be used, and we will adopt this choice. As far as the transmission performance evaluation is concerned, we will still use Equation 10.22, but without the constraint of considering only linear phenomena. The main problem in considering LH systems in a transparent network is that the dis- persion map cannot be really optimized, since it is not a priori known what will be the routes of the channels passing from a certain link This uncertainty also thwarts the use of predistortion based on back-propagation and of all the similar electronic compensation methods, due to the fact that the channel could change the routing through the network. We will solve this problem simply by placing in the receiver, a strong adaptive nine taps Feed Forward Equalizer (FFE) + nine taps Decision Driven Equalizer (DFE) electronic compensator. This component introduces a back-to-back penalty, but assures a good blind compensation of all the ISI sources. A slight dispersion under-compensation will be operated in any case in every single span. This will damage short links, but will be beneficial for longer ones that are at greater risk from a transmission point of view. Since a further crosstalk contribution is added by the OXCs, the channel spacing will be 100 GHz with a bit rate of 10 Gbit/s. In synthesis, the penalties we will consider in the case of NRZ modulation, that is the only case that we consider here, are summarized in Table 10.4, besides a few needed sys- tem parameters. TABLE 10.4 Penalties in the Case of NRZ Modulation and a Few System Parameters System Transmitted power DBR tunable with integrated SOA 16 dBm Power injected in AWG, modulator and passives loss Fiber Reference SN, 12 dB pre-FEC (used ITU-T standard FEC) Optical bandwidth Depends on the number of OXC Cascading effect Penalties Trans