Dynamic call model prediction
AssigneeMicrosoft Technology Licensing, LLC
InventorsTasneem Khuzema Naseem, Steven Rhejohn Barlin So, Philip To
Life of this patent
Estimating the term…
Abstract
A call model is generated that takes into account location-specific information and target attributes such as throughput per user. A cluster of different machine learning models is utilized to compute dynamic call model characteristics for each location, and merges the outputs into a dynamic call model. Additionally, techniques such as feature vector extraction, clustering algorithms, and ensemble models are employed to improve the accuracy and predictive performance of the machine learning models.
Claims20
A method of generating a call model usable by a telecommunications network operator to model network usage, the method comprising:
- receiving, by a computing system, site data indicative of a location where a user plane and control plane is to be deployed in a telecommunications network, wherein the site data comprises location-specific information associated with the location;
- determining a plurality of target attributes indicative of capabilities of the telecommunications network;
- inputting the site data to a dynamic call model predictor, wherein the dynamic call model predictor comprises a plurality of different machine learning models that are each configured to generate a dynamic call model characteristic associated with one of the plurality of target attributes;
- merging the dynamic call model characteristics generated by the plurality of different machine learning models of the dynamic call model predictor into a dynamic call model, wherein the dynamic call mode characteristics are merged to correspond to a representation of computing and network resources of the telecommunications network;
- and
- using the dynamic call model to allocate computing and network capacity in the telecommunications network.
A computing system, comprising:
- one or more processors;
- and
- a computer-readable storage medium having computer-executable instructions stored thereupon which, when executed by the processor, cause the computing system to perform operations comprising:
- accessing site data indicative of a location where a user plane and control plane is to be deployed in a telecommunications network, wherein the site data comprises location-specific information associated with the location;
- inputting the site data to a dynamic call model predictor, wherein the dynamic call model predictor comprises a plurality of different machine learning models that are each configured to generate a dynamic call model characteristic associated with one of a plurality of target attributes indicative of capabilities of the telecommunications network;
- merging the dynamic call model characteristics generated by the plurality of different machine learning models of the dynamic call model predictor into a dynamic call model;
- and
- using the dynamic call model to allocate computing and network capacity in the telecommunications network.
A computer-readable storage medium having computer-executable instructions stored thereupon which, when executed by a processor of a computing system, cause the computing system to perform operations comprising:
- receiving site data indicative of a location where a user plane and control plane is to be deployed in a telecommunications network, wherein the site data comprises location-specific information associated with the location;
- receiving a plurality of target attributes indicative of capabilities of the telecommunications network;
- inputting the site data to a dynamic call model predictor, wherein the dynamic call model predictor comprises a plurality of different machine learning models that are each configured to generate a dynamic call model characteristic associated with one of the plurality of target attributes;
- merging the dynamic call model characteristics generated by the plurality of different machine learning models of the dynamic call model predictor into a dynamic call model, wherein the dynamic call mode characteristics are merged to correspond to a representation of computing and network resources of the telecommunications network;
- and
- outputting the dynamic call model to allocate computing and network capacity in the telecommunications network.
Dependencies are inferred from the claim text.