## 3 Models and Algorithms
### Lightpath Provisioning
We observe that the first-fit approach provided the highest number of connection requests blocked in all the cases because the channel selected could not provide acceptable QoT, i.e., blocking was not a consequence of a lack of available channels in the selected route. The final blocking ratio was as high as 34% after processing 1000 connection requests. The number of requests blocked was highly reduced by 54% (from 344 down to 156) when the OCATA-assisted on-line MB-RSA algorithm (Algorithm 4) was applied to find the best channel that could provide the needed QoT. In this case, the final blocking ratio reduced to 15.6%. Finally, when the NLI noise mitigation technique was also implemented, the number of requests blocked, remarkably reduced by an additional 56% (from 156 down to 68), with a final blocking ratio of just 6.8%. Hence, the total blocking reduction when the NLI noise mitigation technique is implemented is over 80%. Figure 13: Spanish core optical network topology (**a**). Number of demands blocked (**b**) and blocking ratio evolution (**c**) vs. demand number. ## 5 Concluding Remarks

A digital twin-assisted lightpath provisioning approach has been proposed for providing route and channel assignment that can provide the required QoT in multiband optical networks. The particular impact of nonlinear impairments on each optical channel in the spectrum of the C+L+S transmission bands makes channel assignment a non-trivial problem, with a huge impact on the network resource utilization and thus on the capability of the network to provide optical connections. In view of that, the OCATA-MB time domain digital twin is proposed, not only to provide QoT estimation of a given route and a channel assignment, but also to actively participate in the channel assignment itself. OCATA includes DNNs modeling optical signal propagation in optical networks. Because of the different impact of nonlinear noise on the different channels and the large number of channels available in the C+L+S MB transmission systems, OCATA-MB includes a special methodology that defines reference channels to reduce the number of DNN models and a feature composition block that provides the features for any target channel by interpolating those of the two adjacent reference channels. It is worth noting that the number of considered reference channels plays an important role in the accuracy of the procedure, as well in the scalability of the OCATA-MB methodology. Therefore, an algorithm is proposed to define the number and identify the reference channels to be used for DNN modeling. Finally, nonlinear mitigation is proposed to improve the QoT of optical connections by optimizing the detection areas in the Rx. NLI noise mitigation can then be used in the case that a lightpath cannot be provisioned because none of the available channels can provide the required QoT, and therefore such nonlinear mitigation is a valuable tool to reduce connection blocking. The performance of the proposed OCATA-MB methodology was assessed using numerical simulation. The results showed remarkable accuracy in the estimation of the features of the reference channels after they were propagated by the DNN models, as well as for the non-reference channels whose features were estimated from the RChs. The accuracy of the proposed approach was demonstrated when estimating the QoT, specifically the pre-FEC BER. The performance of the nonlinear noise mitigation technique was also assessed, and the results showed an important improvement in the QoT for different channel assignments. Finally, the performance of the proposed OCATA-MB-assisted lightpath provisioning approach was evaluated, and the results showed an over 50% improvement in terms of the blocking ratio w.r.t. a traditional first-fit algorithm with QoT estimation when NLI noise mitigation was not implemented, and an additional 50% of improvement when the NLI noise mitigation was applied. The obtained results clearly show the usefulness of the proposed methodology. Conceptualization, L.V., J.P. and M.R. ; methodology, L.V.