Abstract: Aspects of the subject disclosure may include, for example, predicting dense wavelength division multiplexing (DWDM) path outage prediction and recommendation of alternate communication paths. Parameterized DWDM signals are launched, and resulting network characteristics are determined. The parameters and characteristics are used to train one or more machine learning models subsequently used to predict outages and recommend alternate paths. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device, including: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: determining a network topology in a fiber optic network, wherein the network topology comprises a plurality of network elements joined by fiber optic links; selecting parameter values of a set of parameters for a channel between a first network element and a second network element in the plurality of network elements; applying the parameter values to create parameterized dense wavelength division multiplexing (DWDM) signals between the first network element and the second network element; responsive to the applying the parameter values, determining characteristics of the channel in the fiber optic network; repeating the selecting and applying of the parameter values to determine the characteristics of the channel using different selected parameter values

Abstract: Aspects of the subject disclosure may include, for example, receiving network information about physical parameters of a fronthaul network of a mobility network, the fronthaul network including multiple network elements including optical communication elements of a radio access network of the mobility network, forming collected network information, receiving from a deep learning (DL) model, operating parameters for a channel in the fronthaul network, the operating parameters determined by the DL model for improved spectral efficiency in the channel between a first element and a second element in the fronthaul network, and launching the channel between the first element and the second element, wherein the launching the channel is according to the operating parameters. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, identifying network elements of a wavelength division multiplexing (WDM) domain of an optical waveguide communication system that includes a group of optical-add-drop multiplexor (OADM) devices. Operations are observed for the WDM domain configured to deliver communication services configured for simultaneously transporting independent signals across a network of single optical waveguides. A demand for optical waveguide communication services is determined and the WDM network is configured according to the optical fiber communication link requirement and according to the observations. The configured WDM network includes at least one OADM device of the group of OADM devices configured to provide a WDM cross-frequency network path of the configured WDM network. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device, including: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: determining a network topology in a fiber optic network, wherein the network topology comprises a plurality of network elements joined by fiber optic links; selecting parameter values of a set of parameters for a channel between a first network element and a second network element in the plurality of network elements; applying the parameter values to create parameterized dense wavelength division multiplexing (DWDM) signals between the first network element and the second network element; responsive to the applying the parameter values, determining characteristics of the channel in the fiber optic network; repeating the selecting and applying of the parameter values to determine the characteristics of the channel using different selected parameter values

Abstract: Aspects of the subject disclosure may include, for example, identifying network elements of a wavelength division multiplexing (WDM) domain of an optical waveguide communication system that includes a group of optical-add-drop multiplexor (OADM) devices. Operations are observed for the WDM domain configured to deliver communication services configured for simultaneously transporting independent signals across a network of single optical waveguides. A demand for optical waveguide communication services is determined and the WDM network is configured according to the optical fiber communication link requirement and according to the observations. The configured WDM network includes at least one OADM device of the group of OADM devices configured to provide a WDM cross-frequency network path of the configured WDM network. Other embodiments are disclosed.

Abstract: Devices, computer-readable media, and methods for automatically configuring network elements in multi-vendor and multi-domain topologies. In one example, a method includes determining a need of a communications network, where a topology of the communications network includes a plurality of network functions from at least two different vendors, predicting a subset of the plurality of network functions and respective configuration parameter values for network functions in the subset, that are expected to support the need of the communications network, and modifying the configurations of the network functions in the subset to reflect the respective configuration parameter values.

Abstract: Devices, computer-readable media, and methods for automatically configuring network elements in multi-vendor and multi-domain topologies. In one example, a method includes determining a need of a communications network, where a topology of the communications network includes a plurality of network functions from at least two different vendors, predicting a subset of the plurality of network functions and respective configuration parameter values for network functions in the subset, that are expected to support the need of the communications network, and modifying the configurations of the network functions in the subset to reflect the respective configuration parameter values.

Abstract: Devices, computer-readable media, and methods for automatically configuring network elements in multi-vendor and multi-domain topologies. In one example, a method includes determining a need of a communications network, where a topology of the communications network includes a plurality of network functions from at least two different vendors, predicting a subset of the plurality of network functions and respective configuration parameter values for network functions in the subset, that are expected to support the need of the communications network, and modifying the configurations of the network functions in the subset to reflect the respective configuration parameter values.

Abstract: Aspects of the subject disclosure may include, for example, discovering a network topology of a radio access network (RAN) domain of a cellular communication system, including a base station and a wireless backhaul. The base station includes a centralized unit and distributed units configured for wireless communication with user equipment and, via the wireless backhaul, with the centralized unit. Operation of the RAN domain is observed, wherein the wireless backhaul includes at least one distributed unit in wireless communication with the centralized unit, and in further communication with a core network via the centralized unit. A demand for a cellular communication service is determined and the wireless backhaul is configured according to the demand and the observations. The configured wireless backhaul network includes the at least one distributed unit of the number of distributed units in wireless communication with the centralized unit. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, identifying network elements of a wavelength division multiplexing (WDM) domain of an optical waveguide communication system that includes a group of optical-add-drop multiplexor (OADM) devices. Operations are observed for the WDM domain configured to deliver communication services configured for simultaneously transporting independent signals across a network of single optical waveguides. A demand for optical waveguide communication services is determined and the WDM network is configured according to the optical fiber communication link requirement and according to the observations. The configured WDM network includes at least one OADM device of the group of OADM devices configured to provide a WDM cross-frequency network path of the configured WDM network. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device, including: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: determining a network topology in a fiber optic network, wherein the network topology comprises a plurality of network elements joined by fiber optic links; selecting parameter values of a set of parameters for a channel between a first network element and a second network element in the plurality of network elements; applying the parameter values to create parameterized dense wavelength division multiplexing (DWDM) signals between the first network element and the second network element; responsive to the applying the parameter values, determining characteristics of the channel in the fiber optic network; repeating the selecting and applying of the parameter values to determine the characteristics of the channel using different selected parameter values

Abstract: Aspects of the subject disclosure may include, for example, predicting dense wavelength division multiplexing (DWDM) path outage prediction and recommendation of alternate communication paths. Parameterized DWDM signals are launched, and resulting network characteristics are determined. The parameters and characteristics are used to train one or more machine learning models subsequently used to predict outages and recommend alternate paths. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, collecting network information for a mobility network, including processing the network information at a central controller serving the mobility network, building, in the central controller, a machine learning model including building the machine learning model using the network information, and allocating, by the central controller, radio channels of the mobility network based on a recommendation of the machine learning model. Other embodiments are disclosed.

Abstract: Systems and methods for self-characterization of a software-defined optical network are disclosed. A test transponder may generate and transmit test traffic using various combinations of transmission parameters to discern physical characteristic of a route between two network elements. The test transponder may compute optical characteristics of the route based on the physical characteristics and transmission parameters. An SDN controller may maintain a characterization database storing test results. The test results may be fed to a machine learning engine, which outputs predictions or recommendations regarding utilization of bandwidth and other resources. The optical network may be adapted to handle requested, observed, or predicted changes in on-demand traffic or traffic surges. The test results may be used to defragment the optical spectrum with minimal or no impact on existing traffic to make space in a flexible grid for newly launched channels or channels being moved to different spectrum locations.