Smart and dynamic optical network spectral efficient channel

A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, the operations comprising:

• determining a topology of a network, wherein the network includes a plurality of nodes and at least one optical network-based fronthaul;
• for one or more network paths associated with one or more of the plurality of nodes identified based on the topology, applying one or more sets of parameters to one or more components associated with that network path;
• collecting data relating to the network based on the applying the one or more sets of parameters;
• training one or more deep learning (DL) models using the data, resulting in one or more trained DL models;
• and
• utilizing the one or more trained DL models to generate one or more predictions regarding spectral efficiency relating to the at least one optical network-based fronthaul.

A method, comprising:

• obtaining, by a processing system including a processor, information regarding a topology of a network, wherein the network includes a plurality of nodes and at least one optical network-based fronthaul, at least one optical network-based midhaul, or a combination thereof;
• for one or more routes associated with one or more of the plurality of nodes identified based on the topology, applying, by the processing system, one or more sets of parameters to one or more components associated with that route;
• performing, by the processing system, testing of the network to obtain data relating to the network based on the applying the one or more sets of parameters;
• training, by the processing system, one or more machine learning (ML) models using at least a portion of the data, resulting in one or more trained ML models;
• leveraging, by the processing system, the one or more trained ML models to generate one or more predictions regarding spectral efficiency relating to the at least one optical network-based fronthaul, the at least one optical network-based midhaul, or the combination thereof;
• and
• causing, by the processing system, one or more adjustments to be made to at least a portion of the network based on the one or more predictions.