Systems and methods of a digital twin network for communicating with virtual world environments

1 . A method for building a digital twin network of a modular synthetic digital modeling system of a telecommunications network, the method comprising:

identifying a set of actual network services of a telecommunications network, each actual network service comprising a required data schema format for transmitting data via the network service;

for each data payload type in a set of submissible data payload types originating from a virtual world environment:

identifying a set of compliant network services from the set of actual network services,

wherein the data payload type satisfies the required data schema format for each compliant network service,

determining, via a generative machine learning model, a set of non-compliant network services from the set of actual network services that correspond to required data schema formats with high content similarity to the data payload type,

wherein the data payload type fails to satisfy the required data schema format for each non-compliant network service, and

assigning, from context parameters of the virtual world environment that are available for submission with the data payload type, a set of required context parameters for each network service from the set of compliant network services and the set of non-compliant network services;

generating a service modality configuration that maps each submissible data payload type of the virtual world environment to a set of available network services of the telecommunications network that comprises the set of compliant network services and the set of non-compliant network services;

creating, based on the service modality configuration, the digital twin network including a set of synthetic network services that correspond to the set of available network services,

wherein a runtime configuration of each synthetic network service is functionally similar to the runtime configuration of the corresponding available network service;

receiving real-time performance data samples from the available network services of the telecommunications network, each data sample comprising a source data payload and a first time-series measurement of at least one monitored key performance indicator (KPI) for an actual network service used to transmit the source data payload; and

for each data sample from the real-time performance data samples:

identifying a target synthetic network service of the digital twin network that corresponds to the actual network service used to transmit the data payload,

responsive to transmitting the source payload via the target synthetic network service of the digital twin network, generating a second time-series measurement of the at least one monitored KPI for the target synthetic network service,

determining, using the first and the second time-series measurements of the at least one monitored KPI, a performance similarity score between the actual network service and the target synthetic network, and

when the performance similarity score exceeds a tolerance threshold, applying an adjustment to the runtime configuration of the target synthetic network that causes runtime performance of the at least one monitored KPI for the synthetic network service to match the runtime performance of the at least one monitored KPI for the actual network service.

2 . The method of claim 1 , wherein the adjustment applied to the runtime configuration of the target synthetic network comprises an addition of new network service features, a removal of network service features, a temporary pause of network service features, an adjustment to network service parameters, an update to a prior configuration version of the network service, operations of a self-organizing network (SON), modifications based on standardized algorithms, or a combination thereof.

3 . The method of claim 1 , wherein transmitting the source payload via the digital twin network further comprises:

determining, using the service modality configuration, a required data schema for the source data payload of the target synthetic network service; and

responsive to the source data payload not satisfying the required data schema for the source data payload, prompting a generative machine learning model to generate a modified data payload comprising translated contents of the source data payload that satisfy the required data schema.

4 . The method of claim 1 , further comprising:

for each second data payload type in a second set of submissible data payload types originating from a second virtual world environment:

identifying a second set of compliant network services from the set of actual network services,

wherein the second data payload type satisfies the required data schema format for each compliant network service,

determining, via a generative machine learning model, a second set of non-compliant network services from the set of actual network services that correspond to required data schema formats with high content similarity to the second data payload type,

wherein the second data payload type fails to satisfy the required data schema format for each non-compliant network service, and

assigning, from context parameters of the second virtual world environment that are available for submission with the second data payload type, a second set of required context parameters for each network service from the set of compliant network services and the set of non-compliant network services; and

updating the service modality configuration to map each second data payload type of the second virtual world environment to a second set of available network services of the telecommunications network that comprises the second set of compliant network services and the second set of non-compliant network services.

5 . The method of claim 1 ,

wherein the digital twin network is a first digital twin network configured to execute a first set of user requests for transmitting data from the virtual world environment, and

wherein the method further comprises:

creating, based on the service modality configuration, a second digital twin network including the set of synthetic network services of the first digital twin network that correspond to the set of available network services,

wherein the second digital twin network is configured to execute a second set of user requests for transmitting data from the virtual world environment.

6 . The method of claim 1 , further comprising:

receiving at least one virtual user identifier that corresponds to at least one subscribing user of the virtual world environment;

identifying a network user identifier of a subscribing user of the telecommunications network that is associated with the at least one virtual user identifier of the virtual world environment;

determining, using the network user identifier, a set of prior network services used by the subscribing user of the telecommunications network; and

generating a second modality configuration that maps each submissible data payload type of the virtual world environment to a subset of available network services of the telecommunications network that are included in the set of prior network services.

7 . A non-transitory, computer-readable storage medium comprising instructions recorded thereon that, when executed by at least one processor of a modular synthetic modeling system of a wireless telecommunications network, cause the modular synthetic modeling system to:

receive, via an application programming interface (API), a user request from a virtual world environment for transmitting data using synthetic network services of a digital twin network of the telecommunications network,

wherein the user request comprises a virtual user identifier, a data payload, and a set of request context parameters associated with the virtual world environment;

determine a network user identifier of a subscribing user of the telecommunications network that is associated with the virtual user identifier of the user request from the virtual world environment;

access, using the network user identifier, a service modality configuration of the digital twin network that maps the data payload to a set of available synthetic network services,

wherein each available synthetic network service comprises a set of required context parameters associated with the virtual world environment;

select, from the set of available synthetic network services of the service modality configuration, a synthetic network service of the digital twin network for transmitting the data payload,

wherein the set of request context parameters of the user request satisfies the set of required context parameters of the selected synthetic network service, and

wherein the synthetic network service of the digital twin network corresponds to an actual network service of the telecommunications network;

transmit, via the selected synthetic network service of the digital twin network, the data payload of the user request; and

responsive to at least one monitored key performance indicator (KPI) for the selected synthetic network service of the digital twin network exceeding a tolerance threshold:

identify a first runtime configuration of the synthetic network service of the digital twin network and a second runtime configuration of the actual network service of the telecommunications network,

wherein the first runtime configuration is associated with the at least one monitored KPI for the synthetic network service, and

wherein the second runtime configuration is functionally similar to the first runtime configuration,

apply a corrective adjustment to the first runtime configuration of the synthetic network service of the digital twin network,

wherein the corrective adjustment causes runtime performance of the at least one monitored KPI to be within the tolerance threshold, and

apply the corrective adjustment to the second runtime configuration of the actual network service of the telecommunications network.

8 . The non-transitory, computer-readable storage medium of claim 7 , wherein the instructions further cause the modular synthetic modeling system to:

responsive to at least one monitored KPI for the actual network service of the telecommunications network exceeding a second tolerance threshold:

identify a third runtime configuration of the actual network service of the telecommunications network and a fourth runtime configuration of the synthetic network service of the digital twin network,

wherein the third runtime configuration is associated with the at least one monitored KPI for the actual network service, and

wherein the fourth runtime configuration is functionally similar to the third runtime configuration,

apply a second corrective adjustment to the third runtime configuration of the actual network service of the telecommunications network,

wherein the second corrective adjustment causes runtime performance of the at least monitored KPI of the actual network service to be within the second tolerance threshold, and

apply the second corrective adjustment to the fourth runtime configuration of the synthetic network service of the digital twin network.

9 . The non-transitory, computer-readable storage medium of claim 7 ,

wherein the user request from the virtual world environment further comprises a recipient user identifier of a recipient subscribing user of the telecommunications network, and

wherein the instructions that cause the modular synthetic modeling system to transmit the data payload of the user request further cause the modular synthetic modeling system to:

present, at a user interface of the recipient subscribing user, contents of the data payload of the user request.

10 . The non-transitory, computer-readable storage medium of claim 9 ,

wherein the recipient user identifier is a second virtual user identifier of a second virtual world environment, and

wherein the instructions further cause the modular synthetic modeling system to:

determine a second network user identifier of the recipient subscribing user that is associated with the second virtual user identifier;

identify a set of recipient context parameters associated with the second virtual world environment;

access, using the second network user identifier, a second service modality configuration that maps the selected synthetic network service of the digital twin network to a set of available data formats of the data payload,

wherein each available data format comprises a set of required context parameters associated with the second virtual world environment;

select, from the set of available data formats of the service modality configuration, a data format for presenting the data payload at the user interface of the recipient subscribing user,

wherein the set of recipient context parameters satisfies the set of required context parameters of the selected data format; and

configure the contents of the data payload of the user request to be presented according to the selected data format.

11 . The non-transitory, computer-readable storage medium of claim 7 , wherein the instructions that further cause the modular synthetic modeling system to:

determine, from the synthetic network service of the digital twin network, a first service consumption rate representative of approximate usage of the synthetic network service by subscribing users of the virtual world environment;

determine, from the actual network service of the telecommunications network, a second service consumption rate representative of approximate usage of the network service by subscribing users of the telecommunications network;

estimate, using the first and the second service consumption rates, an equivalence factor for scaling the first service consumption rate of the synthetic network service to match the second service consumption rate of the actual network service; and

adjust the tolerance threshold of the at least one monitored KPI for the synthetic network service based on the equivalence factor.

12 . The non-transitory, computer-readable storage medium of claim 7 , wherein the instructions further cause the modular synthetic modeling system to:

determine, from the service modality configuration, a required data schema for the data payload when transmitting via the selected synthetic network service of the digital twin network; and

responsive to the data payload not satisfying the required data schema, prompt a generative machine learning model to generate a modified data payload comprising translated contents of the data payload that satisfy the required data schema.

13 . The non-transitory, computer-readable storage medium of claim 7 , wherein the instructions further cause the modular synthetic modeling system to:

determine, using the network user identifier, a set of actual network services previously used by the subscribing user of the telecommunications network;

prompt, using the set of actual network services, a generative machine learning model to identify at least one actual network service that comprises a required data schema relevant to contents of the data payload;

determine, from the digital twin network, at least one synthetic network service that corresponds to the identified at least one actual network service of the telecommunications network; and

responsive to an absence of the at least one synthetic network service from the service modality configuration, add the at least one synthetic network service to the set of available synthetic network services for transmitting the data payload.

14 . The non-transitory, computer-readable storage medium of claim 7 , wherein the instructions further cause the modular synthetic modeling system to:

receive, from an authorized user via a user interface, a temporary adjustment of runtime configurations for a set of target synthetic network services of the digital twin network,

wherein the temporary adjustment is configured to cause, for each target synthetic network service, at least one of:

(1) a termination of network service features,

(2) an embedding of erroneous network service features, or

(3) a security vulnerability of network service features;

responsive to applying the temporary adjustment to the runtime configurations for the set of target synthetic network services, monitor at least one target KPI for each target synthetic network service; and

display, at the user interface, a real-time performance report of the monitored at least one target KPI for the set of target synthetic network services.

15 . The non-transitory, computer-readable storage medium of claim 14 , wherein the instructions further cause the modular synthetic modeling system to:

when the monitored at least one target KPI for at least one target synthetic network service exceeds a target tolerance threshold, prompt a generative machine learning model to generate a set of recommended corrective adjustments for causing runtime performance of the at least one monitored KPI to be within the target tolerance threshold; and

display, at the user interface, the set of recommended corrective adjustments alongside the real-time performance report.

16 . The non-transitory, computer-readable storage medium of claim 7 , wherein the corrective adjustment applied to the first and the second runtime configurations comprises an addition of new network service features, a removal of network service features, a temporary pause of network service features, an adjustment to network service parameters, an update to a prior configuration version of the network service, operations of a self-organizing network (SON), modifications based on standardized algorithms, or a combination thereof.

17 . The non-transitory, computer-readable storage medium of claim 7 , wherein the network user identifier of the subscribing user of the telecommunications network comprises a Mobile Station International Subscriber Directory Number (MSISDN), an International Mobile Subscriber Identity (IMSI), an International Mobile Equipment Identity (IMEI), an Integrated Circuit Card Identifier (ICCID), a Temporary Mobile Subscriber Identity (TMSI), a Globally Unique Temporary Identifier (GUTI), or a combination thereof.

18 . The non-transitory, computer-readable storage medium of claim 7 , wherein the set of request context parameters associated with the virtual world environment comprises a location, a timestamp, a set of movement parameters for entities of the virtual world environment, a set of local environment parameters, a specified network service feature, a set of accessible user interface elements, or a combination thereof.

19 . A modular synthetic modeling system of a wireless telecommunications network comprising:

at least one hardware processor; and

at least one non-transitory memory storing instructions, which, when executed by the at least one hardware processor, cause the modular synthetic modeling system to:

receive, via an application programming interface (API), a user request from a virtual world environment for transmitting data using synthetic network services of a digital twin network of the telecommunications network,

wherein the user request comprises a virtual user identifier, a data payload, and a set of request context parameters associated with the virtual world environment;

determine a network user identifier of a subscribing user of the telecommunications network that is associated with the virtual user identifier of the user request from the virtual world environment;

access, using the network user identifier, a service modality configuration of the digital twin network that maps the data payload to a set of available synthetic network services,

wherein each available synthetic network service comprises a set of required context parameters associated with the virtual world environment;

select, from the set of available synthetic network services of the service modality configuration, a synthetic network service of the digital twin network for transmitting the data payload,

wherein the set of request context parameters of the user request satisfies the set of required context parameters of the selected synthetic network service, and

wherein the synthetic network service of the digital twin network corresponds to an actual network service of the telecommunications network;

transmit, via the selected synthetic network service of the digital twin network, the data payload of the user request; and

responsive to at least one monitored key performance indicator (KPI) for the selected synthetic network service of the digital twin network exceeding a tolerance threshold:

identify a first runtime configuration of the synthetic network service of the digital twin network and a second runtime configuration of the actual network service of the telecommunications network,

wherein the first runtime configuration is associated with the at least one monitored KPI for the synthetic network service, and

wherein the second runtime configuration is functionally similar to the first runtime configuration,

apply a corrective adjustment to the first runtime configuration of the synthetic network service of the digital twin network,

wherein the corrective adjustment causes runtime performance of the at least one monitored KPI to be within the tolerance threshold, and

apply the corrective adjustment to the second runtime configuration of the actual network service of the telecommunications network.