6.2A Procedure for ML Model Provisioning

23.2883GPPArchitecture enhancements for 5G System (5GS) to support network data analytics servicesRelease 18TS

Tools: ARFCN - Frequency Conversion for 5G NR/LTE/UMTS/GSM

6.2A.0 General

This clause presents the procedure for the ML Model provisioning.

An NWDAF containing AnLF may be locally configured with (a set of) IDs of NWDAFs containing MTLF and the Analytics ID(s) supported by each NWDAF containing MTLF to retrieve trained ML models or may use the NWDAF discovery procedure specified in clause 5.2 for discovering NWDAFs containing MTLF. An NWDAF containing MTLF may determine that further training for an existing ML model is needed when it receives the ML model subscription or the ML model request.

NOTE: ML Model provisioning/sharing between multiple MTLFs is not supported in this Release of the specification.

6.2A.1 ML Model Subscribe/Unsubscribe

The procedure in Figure 6.2A.1-1 is used by an NWDAF service consumer, i.e. an NWDAF containing AnLF to subscribe/unsubscribe at another NWDAF, i.e. an NWDAF containing MTLF, to be notified when ML Model Information on the related Analytics becomes available, using Nnwdaf_MLModelProvision services as defined in clause 7.5. The ML Model Information is used by an NWDAF containing AnLF to derive analytics. The service is also used by an NWDAF to modify existing ML Model Subscription(s). An NWDAF can be at the same time a consumer of this service provided by other NWDAF(s) and a provider of this service to other NWDAF(s).

Figure 6.2A.1-1: ML Model for analytics subscribe/unsubscribe

1. The NWDAF service consumer (i.e. an NWDAF containing AnLF) subscribes to, modifies, or cancels subscription for a (set of) trained ML Model(s) associated with a/an (set of) Analytics ID(s) by invoking the Nnwdaf_MLModelProvision_Subscribe / Nnwdaf_MLModelProvision_Unsubscribe service operation. The parameters that can be provided by the NWDAF service consumer are listed in clause 6.2A.2. The service consumer optionally indicates its support for multiple ML models if available.

When a subscription for a trained ML model associated with an Analytics ID is received, the NWDAF containing MTLF may:

– determine whether existing trained ML Model(s) can be used for the subscription; or

– determine whether triggering further training for the existing trained ML models is needed for the subscription.

If the NWDAF containing MTLF determines that further training is needed, this NWDAF may initiate data collection from NFs, (e.g. AMF/DCCF/ADRF), UE Application (via AF) or OAM as described in clause 6.2, to generate the ML model.

If the service invocation is for a subscription modification or subscription cancelation, the NWDAF service consumer includes an identifier (Subscription Correlation ID) to be modified in the invocation of Nnwdaf_MLModelProvision_Subscribe.

2. If the NWDAF service consumer subscribes to a (set of) trained ML model(s) associated to a (set of) Analytics ID(s), the NWDAF containing MTLF notifies the NWDAF service consumer with:

– the trained ML Model Information (containing a (set of) file address(es) of the trained ML model(s)), when multiple ML models is not supported by the consumer; or

– a set of pair of unique ML Model Identifier and ML Model Information associated with an Analytics ID, when multiple ML models is supported by the consumer.

NOTE 1: The structure and format of the ML Model identifier and its uniqueness are up to stage 3.

NOTE 2: Parameters defined for Multiple models are for Analytics accuracy enhancement.

by invoking Nnwdaf_MLModelProvision_Notify service operation. The content of trained ML Model Information that can be provided by the NWDAF containing MTLF is specified in clause 6.2A.2.

The NWDAF containing MTLF also invokes the Nnwdaf_MLModelProvision_Notify service operation to notify an available re-trained ML model when the NWDAF containing MTLF determines that the previously provided trained ML Model required re-training at step 1.

When the step 1 is for a subscription modification (i.e. including Subscription Correlation ID), the NWDAF containing MTLF may provide either a new trained ML model different to the previously provided one, or re-trained ML model by invoking Nnwdaf_MLModelProvision_Notify service operation.

6.2A.2 Contents of ML Model Provisioning

The consumers of the ML model provisioning services (i.e. an NWDAF containing AnLF) as described in clause 7.5 and clause 7.6 may provide the input parameters as listed below:

– Information of the analytics for which the requested ML model is to be used, including:

– A list of Analytics ID(s): identifies the analytics for which the ML model is used.

– [OPTIONAL] Use case context: indicates the context of use of the analytics to select the most relevant ML model ML model.

NOTE 1: The NWDAF containing MTLF can use the parameter "Use case context" to select the most relevant ML model, when several ML models are available for the requested Analytics ID(s). The values of this parameter are not standardized.

– [OPTIONAL] ML Model Interoperability Information. This is vendor-specific information that conveys, e.g., requested model file format, model execution environment, etc. The encoding, format, and value of ML Model Interoperable Information is not specified since it is vendor specific information, and is agreed between vendors, if necessary for sharing purposes.

– [OPTIONAL] ML Model Filter Information: enables to select which ML model for the analytics is requested, e.g. S-NSSAI, Area of Interest. Parameter types in the ML Model Filter Information are the same as parameter types in the Analytics Filter Information which are defined in procedures.

– [OPTIONAL] Target of ML Model Reporting: indicates the object(s) for which ML model is requested, e.g. specific UEs, a group of UE(s) or any UE (i.e. all UEs).

– ML Model Reporting Information with the following parameters:

– (Only for Nnwdaf_MLModelProvision_Subscribe) ML Model Reporting Information Parameters as per Event Reporting Information Parameter defined in Table 4.15.1-1, TS 23.502 [3].

– [OPTIONAL] ML Model Target Period: indicates time interval [start, end] for which ML model for the Analytics is requested. The time interval is expressed with actual start time and actual end time (e.g. via UTC time).

– A Notification Target Address (+ Notification Correlation ID) as defined in clause 4.15.1 of TS 23.502 [3], allowing to correlate notifications received from the NWDAF containing MTLF with this subscription.

– [OPTIONAL] Indication of supporting multiple ML models.

– [OPTIONAL] accuracy level of Interest.

Editor’s note: It is FFS if additional parameters are needed for multiple model provisioning.

The NWDAF containing MTLF provides to the consumer of the ML model provisioning service operations as described in clause 7.5 and 7.6, the output information as listed below:

– (Only for Nnwdaf_MLModelProvision_Notify) The Notification Correlation Information.

– ML Model Information, which includes:

– the ML model file address (e.g. URL or FQDN) for the Analytics ID(s), when multiple ML models is not supported; or.

– a set of pair of unique ML Model identifier and the ML model file address (e.g. URL or FQDN) for the Analytics ID(s), if multiple ML models is supported.

– [OPTIONAL] Validity period: indicates time period when the provided ML Model Information applies.

– [OPTIONAL] Spatial validity: indicates Area where the provided ML Model Information applies.

NOTE 2: Spatial validity and Validity period are determined by MTLF internal logic and it is a subset of AoI if provided in ML Model Filter Information and of ML Model Target Period, respectively.

6.2A.3 ML Model request

The procedure in Figure 6.2A.3-1 is used by an NWDAF service consumer, i.e. an NWDAF containing AnLF to request and get from another NWDAF, i.e. an NWDAF containing MTLF ML Model Information, using Nnwdaf_MLModelInfo services as defined in clause 7.6. The ML Model Information is used by an NWDAF containing AnLF to derive analytics. An NWDAF can be at the same time a consumer of this service provided by other NWDAF(s) and a provider of this service to other NWDAF(s).

Figure 6.2A.3-1: ML model Request

1. The NWDAF service consumer (i.e. an NWDAF containing AnLF) requests a (set of) ML Model(s) associated with a/an (set of) Analytics ID(s) by invoking Nnwdaf_MLModelInfo_Request service operation. The parameters that can be provided by the NWDAF Service Consumer are listed in clause 6.2A.2. The service consumer optionally indicates its support for multiple ML models if available.

When a request to an ML Model Information for the Analytics is received, the NWDAF containing MTLF may:

– determine whether existing trained ML Model(s) can be used for the request; or

– determine whether triggering further training for the existing trained ML models is needed for the request.

2. The NWDAF containing MTLF responds to the NWDAF service consumer by invoking Nnwdaf_MLModelInfo_Request response service operation including:

– the ML Model Information containing a (set of) file address(es) of the trained ML model(s) when multiple ML models is not supported by the consumer; or

– a set of pair of unique ML Model identifier and the ML model file address (e.g. URL or FQDN) for the Analytics ID(s). Multiple models may be provisioned for an Analytics ID, if AnLF indicates in the request that multiple ML models are supported.

The content of ML Model Information that can be provided by the NWDAF containing MTLF is specified in clause 6.2A.2.