# US 2025/0097722 A1 · Determination of a machine learning model to be used for a given purpose related to a communication system

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- Number: US 2025/0097722 A1
- Document ID: US20250097722A1
- Status: Published application
- Kind: A1
- Application number: 18/570,636
- Filed: 2022-08-30
- Published: 2025-03-20
- Earliest claimed: 2022-08-30
- Assignees: Rakuten Mobile, Inc.
- Applicants: Rakuten Mobile, Inc.
- Inventors: Shinya KITA
- Web page: https://patentgrep.com/patent/US20250097722A1

## CPC

- H04W 16/22: Traffic simulation tools or models
- G06N 20/00: Machine learning
- H04L 41/147: for predicting network behaviour
- H04L 41/16: using machine learning or artificial intelligence
- H04W 24/02: Arrangements for optimising operational condition
- H04W 24/08: Testing, {supervising or monitoring} using real traffic
- H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)

## Abstract

It is enabled that accurate determination of a machine learning model which is to be used for predicting a performance index value of a communication system and which is suitable for the communication system. A monitor (72) monitors at least one type of performance index value related to the communication System. An AI (70) identifies, for each of a plurality of machine learning models to be used for a given prediction purpose related to the communication system, an additional performance index value type which is a type of performance index value required to be added to a target of the monitoring in order to use the machine learning model. The AI (70) determines at least one machine learning model among the plurality of machine learning models based on the additional performance index value type identified for each of the plurality of machine learning models.

## Claims

### Claim 1

A model determination system, comprising one or more processors, the model determination system causing at least one of the one or more processors to execute:
a monitoring process of monitoring at least one type of performance index value related to a communication system;
an additional performance index value type identification process of identifying, for each of a plurality of machine learning models to be used for a given prediction purpose related to the communication system, an additional performance index value type which is a type of performance index value required to be added to a target of the monitoring in order to use the machine learning model; and
a model determination process of determining at least one machine learning model among the plurality of machine learning models based on the additional performance index value type identified for each of the plurality of machine learning models.

### Claim 2 (depends on 1)

The model determination system according to claim 1, wherein, in the additional performance index value type identification process, for each of the plurality of machine learning models, a type of performance index value not included in the target of the monitoring among types of performance index values which are inputs to the machine learning model is identified as the additional performance index value type.

### Claim 3 (depends on 1)

The model determination system according to claim 1, wherein, in the model determination process, at least one machine learning model among the plurality of machine learning models is determined based on the number of the additional performance index value types.

### Claim 4 (depends on 1)

The model determination system according to claim 1, wherein, in the model determination process, at least one machine learning model among the plurality of machine learning models is determined based on a ratio of the number of the additional performance index value types to the number of types of performance index values to be input to the machine learning model.

### Claim 5 (depends on 1)

The model determination system according to claim 1, wherein the model determination system causes the at least one of the one or more processors to execute a monitoring target addition process of adding, to monitoring targets in the monitoring process, the performance index value of the additional performance index value type which is required to be added in order to use the determined machine learning model.

### Claim 6 (depends on 1)

The model determination system according to claim 1, wherein the model determination system causes the at least one of the one or more processors to execute a prediction process of predicting the performance index value of the communication system by using the determined machine learning model.

### Claim 7

A model determination method, comprising:
monitoring at least one type of performance index value related to a communication system;
identifying, for each of a plurality of machine learning models to be used for a given prediction purpose related to the communication system, an additional performance index value type which is a type of performance index value required to be added to a target of the monitoring in order to use the machine learning model; and
determining at least one machine learning model among the plurality of machine learning models based on the additional performance index value type identified for each of the plurality of machine learning models.