Telecommunication resource deployment using machine learning systems and methods

Patent metadata

Field	Value
Publication number	US-12356207-B2
Application number	US-202217863284-A
Country	US
Kind code	B2
Filing date	Jul 12, 2022
Priority date	Jul 12, 2022
Publication date	Jul 8, 2025
Grant date	Jul 8, 2025

Abstract

System and methods for generating a deployment that uses existing telecommunication resources, such as microservices, data sources, and/or communication channels. The deployment can comprise a digital representation of a base station deployment. A plain language message is received that describes a desired deployment of telecommunication resources. One or more entities are extracted from the plain language message. Based on the extracted entities, the system recommends one or more existing telecommunication resources for use in the desired deployment. In some implementations, recommendations are generated using a machine learning model that generates relevance scores for each of multiple existing telecommunication resources. A selection is received from among the recommended telecommunication resources, and the desired deployment is generated using the selected telecommunication resources.

First claim

We claim:

1. A computing system for generating telecommunications base station deployments using existing resources, the computing system comprising:
at least one hardware processor;
at least one display; and
at least one non-transitory memory carrying instructions that, when executed by the at least one hardware processor, cause the computing system to perform operations to generate a digital representation of a telecommunications base station deployment, the operations comprising:
displaying, at the at least one display, a graphical user interface (GUI) comprising an input region and a recommendation region, wherein the input region of the GUI includes at least one input field;
receiving, via the at least one input field in the input region of the GUI, a plain language message that describes a telecommunications base station deployment,
wherein the telecommunications base station deployment comprises a set of hardware resources;

extracting, from the plain language message that describes the telecommunications base station deployment, at least one entity related to a characteristic of the telecommunications base station deployment,
wherein the at least one entity includes a keyword or phrase;

identifying, based on the extracted at least one entity and using a machine learning model, multiple recommended resources for the telecommunications base station deployment,
wherein at least some of the multiple recommended resources correspond to a hardware resource of the set of hardware resources, and
wherein the multiple recommended resources for the telecommunications base station deployment are identified based on comparing a relevance score generated by the machine learning model for each of multiple existing resources to a corresponding threshold relevance score;

dynamically displaying, at the recommendation region of the GUI, the multiple recommended resources for the telecommunications base station deployment;
receiving, via the GUI, a selection of one or more of the multiple recommended resources to be included in the telecommunications base station deployment; and
generating, by the computing system, a digital representation of the telecommunications base station deployment,
wherein the digital representation of the telecommunications base station deployment includes the selected one or more recommended resources.

2. The computing system of claim 1 :
wherein the GUI further comprises a deployment region, and
wherein the selection of the one or more recommended resources is received by detecting that a user has dragged the one or more recommended resources to the deployment region.

3. The computing system of claim 1 :
wherein the at least one input field of the GUI comprises a first input field to receive the plain language message and a second input field to receive an additional message,
wherein the second input field is displayed in response to receiving a command to add an input field, and
wherein the displayed multiple recommended resources dynamically update in response to receiving the additional message at the second input field.

4. The computing system of claim 1 :
wherein the machine learning model is trained using a training dataset comprising multiple existing resources each associated with at least one existing deployment, and
wherein each of the multiple existing resources in the training dataset is associated with metadata.

5. The computing system of claim 1 :
wherein the machine learning model is trained using a training dataset comprising multiple existing resources each associated with at least one existing deployment,
wherein each of the multiple existing resources in the training dataset is associated with metadata, and
wherein each of the multiple existing resources in the training dataset is represented by a data object that includes the metadata.

6. At least one computer-readable medium, excluding transitory signals, carrying instructions that, when executed by a computing system, cause the computing system to perform operations to generate a deployment using existing telecommunication resources, the operations comprising:
receiving a set of plain language messages that describes a desired deployment comprising multiple telecommunication resources;
extracting, from each plain language message in the set of plain language messages, at least one keyword or phrase related to a characteristic of the desired deployment;
accessing multiple existing telecommunication resources,
wherein the multiple existing telecommunication resources comprise at least one of a data source, a microservice, or a communication channel, and
wherein each of the multiple existing telecommunication resources is associated with metadata related to an existing deployment that includes the existing telecommunication resource;

generating, by a trained machine learning model, a relevance score for each of the accessed multiple existing telecommunication resources,
wherein the relevance score reflects a likelihood that a corresponding existing telecommunication resource is relevant to the desired deployment;

recommending, based on the generated relevance scores, at least some of the multiple existing telecommunication resources for inclusion in the desired deployment;
receiving a selection of two or more telecommunication resources from the recommended at least some of the multiple existing telecommunication resources; and
generating, using the selected two or more telecommunication resources, a set of instructions intended to achieve the desired deployment.

7. The at least one computer-readable medium of claim 6 , wherein the desired deployment includes a digital resource that represents a hardware resource associated with the desired deployment.

8. The at least one computer-readable medium of claim 6 , wherein the set of plain language messages is received at an input region of a graphical user interface (GUI), the operations further comprising:
displaying the recommended at least some of the multiple existing telecommunication resources at a recommendation region of the GUI.

9. The at least one computer-readable medium of claim 6 , the operations further comprising:
displaying the recommended at least some of the multiple existing telecommunication resources at a recommendation region of graphical user interface (GUI),
wherein receiving the selection of the two or more telecommunication resources from the recommended at least some of the multiple existing telecommunication resources includes detecting that a user has dragged the two or more telecommunication resources from the recommendation region of the GUI to a deployment region of the GUI.

10. The at least one computer-readable medium of claim 6 , wherein at least some of the multiple existing telecommunication resources are accessed using data objects that each represent an existing telecommunication resource of the at least some of the multiple existing telecommunication resources.

11. The at least one computer-readable medium of claim 6 :
wherein the desired deployment includes a software product comprising a set of microservices, and
wherein generating the set of instructions intended to achieve the desired deployment includes aggregating software code.

12. The at least one computer-readable medium of claim 6 , wherein the operations further comprise:
identifying a need for at least one additional telecommunication resource for the desired deployment that is not included in the multiple existing telecommunication resources; and
generating a prompt to provide the needed at least one additional telecommunication resource.

13. The at least one

Assignees

• T Mobile Usa Inc

Inventors

• Kadam Salil
• Sharma Devanand
• Hodgen James
• Neelakandasharma Prasad
• Badrinath Surya
• Vijayan Nair Vimalakumari Amma Arun

Classifications

• G06F40/289

  Phrasal analysis, e.g. finite state techniques or chunking · CPC title

• G06F3/0486

  Drag-and-drop · CPC title

• G06F3/04847

  Interaction techniques to control parameter settings, e.g. interaction with sliders or dials · CPC title

• H04W24/02 Primary

  Arrangements for optimising operational condition · CPC title

• G06F40/30

  Semantic analysis · CPC title