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11.2.5 Naf_VFLTraining_Request service operation
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Service operation name: Naf_VFLTraining_Request
Editor´s note: Name of this service operation and its necessity and its content is FFS. It is also FFS whether it can be replaced by a subscription request for the preparation.
Description: In preparation of VFL training, requests NWDAF VFL client to check if it can support requirements for VFL.
Inputs, Required:
- Analytics ID.
Inputs, Optional: None.
Outputs Required: When the request is accepted: list of sample IDs, VFL Interoperability Information. When the request is not accepted, an error response with cause code (e.g. AF does not meet the VFL training requirements.
NOTE: The detail reasons in the cause code are up to Stage 3.
Outputs, Optional:
- Feature ID.
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11.3 Naf_VFLInference Service
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11.3.1 General
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Service Description: This service is provided by AF acting as VFL client and enables an VFL server as consumer to request or subscribe/unsubscribe for a VFL inference.
When the subscription is accepted by the AF, the consumer receives from the NWDAF an identifier (Subscription Correlation ID) allowing to further manage (modify, delete) this subscription.
Editor´s note: Parameters of the service operations are FFS and more will be added when procedures and content of services are agreed.
Editor´s note: It is FFS whether this service is also provided by an AF acting as VFL server to enable a consumer to request Inference
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11.3.2 Naf_VFLInference_Subscribe service operation
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Service operation name: Naf_VFLInference_Subscribe
Description: Subscribe to VFL inference.
Inputs, Required:
For new subscription:
- Notification Target Address (+ Notification Correlation ID).
- VFL Correlation ID.
- Target of VFL inference.
- Analytics ID.
When updating a subscription:
- Subscription Correlation ID.
Inputs, Optional:
- VFL inference filter.
Outputs Required: When the subscription is accepted: Subscription Correlation ID (required for management of this subscription). When the subscription is not accepted, an error response.
Outputs, Optional: Client intermediate results.
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11.3.3 Naf_VFLInference_Unsubscribe service operation
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Service operation name: Naf_VFLInference_Unsubscribe
Description: Unsubscribe to VFL inference.
Inputs, Required: Subscription Correlation ID.
Inputs, Optional: None.
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
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11.3.4 Naf_VFLInference_Notify service operation
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Service operation name: Naf_VFLInference_Notify
Description: Notify VFL inference result.
Inputs, Required:
- Notification Correlation Information.
Inputs, Optional:
- Client intermediate results.
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
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11.3.5 Naf_VFLInference_Request service operation
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Service operation name: Naf_VFLInference_Request
Description: The consumer requests the AF to perform a one-time VFL inference.
Inputs, Required:
- Target of VFL inference.
- VFL Correlation ID.
- Analytics ID.
Inputs, Optional:
- VFL inference filter.
Outputs, Required: If the request is accepted, then client intermediate results. When the request is not accepted, an error response.
Outputs, Optional: None.
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11.4 Naf_Inference Service
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11.4.1 General
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Service Description: This service is provided by AF acting as VFL server and enables an NWDAF or an NEF acting on its behalf as consumer to request or subscribe/unsubscribe for a VFL inference.
Editor's note: Parameters of the service operations are FFS and more will be added when procedures and content of services are agreed.
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11.4.2 Naf_Inference_Subscribe service operation
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Service operation name: Naf_Inference_Subscribe
Description: Subscribe to VFL inference.
Inputs, Required:
For new subscription:
- Notification Target Address (+ Notification Correlation ID).
- Analytics ID.
- Target of Analytics Reporting.
When updating a subscription:
- Subscription Correlation ID.
Inputs, Optional:
- Analytics Reporting Information.
- Analytics Filter.
Outputs Required: When the subscription is accepted: Subscription Correlation ID (required for management of this subscription). When the subscription is not accepted, an error response.
Outputs, Optional: None.
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11.4.3 Naf_Inference_Unsubscribe service operation
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Service operation name: Naf_Inference_Unsubscribe
Description: Unsubscribe to VFL inference.
Inputs, Required: Subscription Correlation ID.
Inputs, Optional: None.
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
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11.4.4 Naf_Inference_Notify service operation
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Service operation name: Naf_Inference_Notify
Description: Notify VFL inference result.
Inputs, Required:
- Notification Correlation Information.
Inputs, Optional:
- VFL inference results.
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
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11.4.5 Naf_Inference_Request service operation
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Service operation name: Naf_Inference_Request
Description: The consumer requests the AF to perform a one-time VFL inference.
Inputs, Required:
- Analytics ID.
- Target of Analytics Reporting.
Inputs, Optional:
- Analytics Reporting Information.
- Analytics Filter.
Outputs, Required: If the request is accepted, then VFL inference results. When the request is not accepted, an error response.
Outputs, Optional: None.
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11.5 Naf_Training Service
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11.5.1 General
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Service Description: This service is provided by an AF acting as VFL server and enables an NWDAF or an NEF acting on its behalf as consumer to request the AF to perform model training as defined in clause 6.2H.2.3 under the supervision of the consumer.
Editor´s note: Parameters of the service operations are FFS and more will be added when procedures and content of services are agreed.
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11.5.2 Naf_Training_Subscribe service operation
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Service operation name: Naf_Training_Subscribe
Description: Subscribes to ML Model training with AF as VFL server.
Inputs, Required:
For new subscription:
- Analytics ID as defined in Table 7.1-2.
- Notification Target Address (+ Notification Correlation ID).
When updating a subscription:
- Subscription Correlation ID.
Inputs, Optional:
Outputs Required: When the request is accepted: Subscription Correlation ID (required for management of this subscription). When the request is not accepted, an error response with cause code.
NOTE: The detail reasons in the cause code are up to Stage 3.
Outputs, Optional: None.
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11.5.3 Naf_Training_Unsubscribe service operation
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Service operation name: Naf_Training_Unsubscribe
Description: Terminate AF ML Model training.
Inputs, Required: Subscription Correlation ID.
Inputs, Optional: None.
Outputs, Required: Operation execution result indication.
Outputs, Optional: Cause code.
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11.5.4 Naf_Training_Notify service operation
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Service operation name: Naf_Training_Notify
Description: AF notifies the consumer of training progress
Inputs, Required:
- Notification Correlation Information.
Inputs, Optional:
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
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12 NEF Services to support network data analytics
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12.1 General
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Table 12.1-1 illustrates the NEF Services to support network data analytics.
Table 12.1-1: NF services provided by NEF to support network data analytics
Service Name
Service Operations
Operation Semantics
Example Consumer(s)
Nnef_VFLTraining
Subscribe
Subscribe / Notify
NWDAF
Unsubscribe
NWDAF
Notify
NWDAF
Preparation
Request / Response
NWDAF
Nnef_VFLInference
Subscribe
Subscribe / Notify
NWDAF
Unsubscribe
NWDAF
Notify
NWDAF
Request
Request / Response
NWDAF
Nnef_VFLNFdiscovery
NwdafDiscovery
Request / Response
AF
NwdafRelease
Request / Response
AF
Nnef_Inference
Subscribe
Subscribe / Notify
NWDAF
Unsubscribe
NWDAF
Notify
NWDAF
Request
Request / Response
NWDAF
Nnef_Training
Subscribe
Subscribe / Notify
NWDAF
Unsubscribe
NWDAF
Notify
NWDAF
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12.2 Nnef_VFLTraining Service
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12.2.1 General
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Service Description: This service is provided by an NEF on behalf of either an NWDAF or AF acting as VFL client in training process as defined in clause 6.2H.2.3.
For VFL, this service may also be used by the consumer (i.e. FL Server) to prepare the VFL training as described in in clause 6.2H.2.2.
Editor´s note: Parameters of the service operations are FFS and more will be added when procedures and content of services are agreed.
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12.2.2 Nnef_VFLTraining_Subscribe service operation
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Service operation name: Nnef_VFLTraining_Subscribe
Description: Subscribes to VFL ML Model training with AF as VFL client.
Inputs, Required:
For new subscription:
- Analytics ID.
- Notification Target Address (+ Notification Correlation ID).
When updating a subscription:
- Subscription Correlation ID.
- For NWDAF as VFL client, external NWDAF ID.
Inputs, Optional:
- Analytics filter information.
- Maximum response time.
- Intermediate training information.
- VFL Correlation ID is added by server at VFL training process start.
- VFL Interoperability Information.
- Feature ID.
Outputs Required: When the request is accepted: Subscription Correlation ID (required for management of this subscription). When the request is not accepted, an error response with cause code.
NOTE: The detail reasons in the cause code are up to Stage 3.
Outputs, Optional:
- Client intermediate training result.
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12.2.3 Nnef_VFLTraining_Unsubscribe service operation
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Service operation name: Nnef_VFLTraining_Unsubscribe
Description: Terminate AF VFL ML Model training.
Inputs, Required: Subscription Correlation ID.
Inputs, Optional: None.
Outputs, Required: Operation execution result indication.
Outputs, Optional: Cause code.
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12.2.4 Nnef_VFLTraining_Notify service operation
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Service operation name: Nnef_VFLTraining_Notify
Description: NEF notifies the consumer of client intermediate training result of the local ML mode.
Inputs, Required:
- Notification Correlation Information.
Inputs, Optional:
- Client intermediate training result.
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
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12.2.5 Nnef_VFLTraining_Request service operation
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Service operation name: Nnef_VFLTraining_Request
Editor´s note: Name of this service operation and its necessity is FFS. It is also FFS whether it can be replaced by a subscription request for the preparation.
Description: In preparation of VFL training, requests NEF to check at untrusted AF acting as VFL client if it can support requirements for VFL.
Inputs, Required:
- Analytics ID.
- For NWDAF as VFL client, external NWDAF ID.
Inputs, Optional: None.
Outputs Required: When the request is accepted: list of sample IDs, VFL Interoperability Information. When the request is not accepted, an error response with cause code (e.g. NWDAF does not meet the VFL training requirements.
NOTE: The detail reasons in the cause code are up to Stage 3.
Outputs, Optional:
- Feature ID.
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12.3 Nnef_VFLInference Service
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12.3.1 General
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Service Description: This service is provided by by an NEF on behalf of an AF acting as VFL client and enables an VFL server as consumer to request or subscribe/unsubscribe for a VFL inference.
When the subscription is accepted by the AF, the consumer receives from the NWDAF an identifier (Subscription Correlation ID) allowing to further manage (modify, delete) this subscription.
Editor´s note: Parameters of the service operations are FFS
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12.3.2 Nnef_VFLInference_Subscribe service operation
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Service operation name: Nnef_VFLInference_Subscribe
Description: Subscribe to VFL inference.
Inputs, Required:
For new subscription:
- Notification Target Address (+ Notification Correlation ID).
- VFL Correlation ID.
- Target of VFL inference.
When updating a subscription:
- Subscription Correlation ID.
- For NWDAF as VFL client, external NWDAF ID.
Inputs, Optional:
- VFL inference filter.
Outputs Required: When the subscription is accepted: Subscription Correlation ID (required for management of this subscription). When the subscription is not accepted, an error response.
Outputs, Optional: Client intermediate results.
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12.3.3 Nnef_VFLInference_Unsubscribe service operation
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Service operation name: Nnef_VFLInference_Unsubscribe
Description: Unsubscribe to VFL inference.
Inputs, Required: Subscription Correlation ID.
Inputs, Optional: None.
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
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12.3.4 Nnef_VFLInference_Notify service operation
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Service operation name: Nnef_VFLInference_Notify
Inputs, Required:
- Notification Correlation Information.
Inputs, Optional:
- Client intermediate results.
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
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12.3.5 Nnef_VFLInference_Request service operation
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Service operation name: Nnef_VFLInference_Request
Description: The consumer requests the NWDAF to perform a one-time VFL inference.
Inputs, Required:
- Target of VFL inference.
- VFL Correlation ID.
- Analytics ID.
Inputs, Optional:
- VFL inference filter.
Outputs, Required: If the request is accepted, then client intermediate results. When the request is not accepted, an error response.
Outputs, Optional: None.
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12.4 Nnef_VFLNFDiscovery Service
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12.4.1 General
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Service Description: This service is provided by by an NEF towards an untrusted AF acting as VFL server to enable the AF to interact with NWDAFs acting as VFL client. It enables the AF to detect NWDAFs as VFL clients as described in in clause 6.2H.2.1.
Editor´s note: Parameters of the service operations are FFS.
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12.4.2 Nnef_VFLNFDiscovery_NwdafDiscovery service operation
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Service operation name: Nnef_VFLNFDiscovery_NwdafDiscovery
Description: The consumer requests the NEF to discover an NWDAF that is to act as VFL client.
Inputs, Required:
- Analytics ID.
- required NF type (i.e. NWDAF type).
- VFL capability type (i.e. VFL client).
Inputs, Optional:
- Required feature IDs.
- Time Period of Interest.
- Optional Service Area.
Outputs, Required: If the request is accepted, external NWDAF ID. When the request is not accepted, an error response.
Outputs, Optional: None.
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12.4.3 Nnef_VFLNFDiscovery_NwdafRelease service operation
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Service operation name: Nnef_VFLNFDiscovery_NwdafDiscovery
Description: The consumer informs the NEF that it mo longer wants .to use an assigned temporary NWDAF ID.
Inputs, Required:
- external NWDAF ID.
Inputs, Optional: None.
Outputs, Required: None.
Outputs, Optional: None.
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12.5 Nnef_Inference Service
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12.5.1 General
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Service Description: This service is provided by an NEF on behalf of an AF acting as VFL server and enables an NWDAF as consumer to request or subscribe/unsubscribe for a VFL inference.
Editor´s note: Parameters of the service operations are FFS.
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12.5.2 Nnef_Inference_Subscribe service operation
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Service operation name: Nnef_Inference_Subscribe
Description: Subscribe to VFL inference.
Inputs, Required:
For new subscription:
- Notification Target Address (+ Notification Correlation ID).
- Analytics ID.
- Target of Analytics Reporting.
When updating a subscription:
- Subscription Correlation ID.
Inputs, Optional:
- Analytics Reporting Information.
- Analytics Filter.
Outputs Required: When the subscription is accepted: Subscription Correlation ID (required for management of this subscription). When the subscription is not accepted, an error response.
Outputs, Optional: None.
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12.5.3 Nnef_Inference_Unsubscribe service operation
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Service operation name: Nnef_Inference_Unsubscribe
Description: Unsubscribe to VFL inference.
Inputs, Required: Subscription Correlation ID.
Inputs, Optional: None.
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
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12.5.4 Nnef_Inference_Notify service operation
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Inputs, Required:
- Notification Correlation Information.
Inputs, Optional:
- VFL inference results.
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
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12.5.5 Nnef_Inference_Request service operation
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Service operation name: Nnef_Inference_Request
Description: The consumer requests the VFL server to perform a one-time VFL inference.
Inputs, Required:
- Analytics ID.
- Target of Analytics Reporting.
Inputs, Optional:
- Analytics Reporting Information.
- Analytics Filter.
Outputs, Required: If the request is accepted, then VFL inference results. When the request is not accepted, an error response.
Outputs, Optional: None.
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12.6 Nnef_Training Service
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12.6.1 General
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Service Description: This service is provided by NEF AF acting on behalf of an untzrusted AF as VFL server and enables an NWDAF as consumer to request the AF to perform model training as defined in clause 6.2H.2.3 under the supervision of the consumer.
Editor´s note: Parameters of the service operations are FFS and more will be added when procedures and content of services are agreed.
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12.6.2 Nnef_Training_Subscribe service operation
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Service operation name: Nnef_Training_Subscribe
Description: Subscribes to ML Model training with AF as VFL server.
Inputs, Required:
For new subscription:
- Analytics ID as defined in Table 7.1-2.
- Notification Target Address (+ Notification Correlation ID).
When updating a subscription:
- Subscription Correlation ID.
Inputs, Optional:
Outputs Required: When the request is accepted: Subscription Correlation ID (required for management of this subscription). When the request is not accepted, an error response with cause code.
NOTE: The detail reasons in the cause code are up to Stage 3.
Outputs, Optional: None.
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12.6.3 Nnef_Training_Unsubscribe service operation
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Service operation name: Nnef_Training_Unsubscribe
Description: Terminate AF ML Model training.
Inputs, Required: Subscription Correlation ID.
Inputs, Optional: None.
Outputs, Required: Operation execution result indication.
Outputs, Optional: Cause code.
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12.6.4 Nnef_Training_Notify service operation
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Service operation name: Nnef_Training_Notify Description: AF notifies the consumer of training progress. Inputs, Required: - Notification Correlation Information. Inputs, Optional: Outputs, Required: Operation execution result indication. Outputs, Optional: None. Annex A (informative): Methods to handle NAT on IPv4 between UE and AF A.1 Methods to handle NAT on IPv4 between UE and AF The following methods can be used to handle the case when there is a NAT between the UE and AF for data collection: NOTE: These methods can be used both when there is a NAT between the UE and the AF, and when there is no NAT between the UE and the AF. 1) Use IPv6 instead of IPv4 and then use any of the procedures in clauses 6.2.8.2.4.2 to 6.2.8.2.4.4. 2) Provide GPSI via header enrichment as described in TS 29.244 [17]. 3) Have GPSI as part of the authentication information, or via in-band signalling. 4) At the establishment of the user plane connection between the UE Application and AF, the AF can use the procedure in clause 4.15.10 of TS 23.502 [3] to get the GPSI. 5) At the establishment of the user plane connection between the UE Application and a trusted AF, the AF can use the steps 3 to 8 in clause 4.15.10 of TS 23.502 [3], where NEF is replaced by the AF, to retrieve the SUPI of the UE. In methods 2) to 4), the AF can correlate the UE public IP address and port with the SUPI/GPSI. Annex B (informative): Change history Change history Date Meeting TDoc CR Rev Cat Subject/Comment New version 2019-05 SP#84 SP-190456 - - - MCC Editorial update for presentation to TSG SA#84 for approval 1.0.0 2019-06 SP#84 - - - - MCC editorial update for publication after approval at TSG SA#84 16.0.0 2019-09 SP#85 SP-190612 0001 3 F Clarifications to Observed Service experience related network data analytics 16.1.0 2019-09 SP#85 SP-190612 0010 1 F Specification clean-up 16.1.0 2019-09 SP#85 SP-190612 0012 3 F Miscellaneous corrections to TS 23.288 16.1.0 2019-09 SP#85 SP-190612 0014 1 F Clarification of NF and AF 16.1.0 2019-09 SP#85 SP-190612 0015 3 F Update the Analytics information provided by NWDAF 16.1.0 2019-09 SP#85 SP-190612 0017 2 F Closing open issue on NEF-AF interaction for data collection from AF 16.1.0 2019-09 SP#85 SP-190612 0026 1 F Clarification of the correlation information 16.1.0 2019-09 SP#85 SP-190612 0027 4 F Clarifications of the pre-check behaviours of the NF 16.1.0 2019-09 SP#85 SP-190612 0029 3 F Corrections to slice load level analytics 16.1.0 2019-09 SP#85 SP-190612 0034 3 F Clarifications on Potential QoS Change 16.1.0 2019-09 SP#85 SP-190612 0036 1 F CR to properly separate UE identifiers from Analytics Filter 16.1.0 2019-09 SP#85 SP-190612 0037 1 F CR for update of observed service experience 16.1.0 2019-09 SP#85 SP-190612 0039 3 F Miscellaneous editorial corrections 16.1.0 2019-09 SP#85 SP-190612 0040 3 F Optionality of data to be collected by NWDAF 16.1.0 2019-09 SP#85 SP-190612 0042 1 F Clarification on Data Collection 16.1.0 2019-09 SP#85 SP-190612 0045 1 F Probability assertion clarification on NWDAF services description 16.1.0 2019-09 SP#85 SP-190612 0046 1 F Corrections for analytics exposure framework related parameters 16.1.0 2019-09 SP#85 SP-190612 0052 1 F BSF and PCF selection for data collection 16.1.0 2019-09 SP#85 SP-190612 0054 - F Corrections to Nnwdaf_AnalyticsSubscription_Subscribe and Nnwdaf_AnalyticsInfo_Request service operations 16.1.0 2019-12 SP#86 SP-191079 0002 6 F Clarifications to NF load data analytics 16.2.0 2019-12 SP#86 SP-191079 0003 8 F Clarifications to Network Performance related network data analytics 16.2.0 2019-12 SP#86 SP-191079 0004 3 F Clarifications to Abnormal behaviour analytics 16.2.0 2019-12 SP#86 SP-191079 0009 4 F Clarifications to UE mobility and Abnormal behaviour analytics 16.2.0 2019-12 SP#86 SP-191079 0043 2 F Remove UE related analytics for any UE 16.2.0 2019-12 SP#86 SP-191079 0044 6 F Clarifications to UE communication and mobility analytics output 16.2.0 2019-12 SP#86 SP-191079 0047 3 F Corrections for observed Service experience related network data analytics 16.2.0 2019-12 SP#86 SP-191079 0055 01 F Terminology Alignment 16.2.0 2019-12 SP#86 SP-191079 0057 5 F Editor's Notes cleanup 16.2.0 2019-12 SP#86 SP-191079 0062 - F Corrections to User Data Congestion Analytics 16.2.0 2019-12 SP#86 SP-191079 0063 - F Correction for data collection from OAM 16.2.0 2019-12 SP#86 SP-191079 0064 7 F Corrections to general and framework parts of analytics 16.2.0 2019-12 SP#86 SP-191079 0065 - F Corrections to data collection from NFs 16.2.0 2019-12 SP#86 SP-191079 0066 6 F Miscellaneous corrections/updates to TS 23.288 16.2.0 2019-12 SP#86 SP-191079 0068 4 F Clarification of the data collection of the OSE 16.2.0 2019-12 SP#86 SP-191079 0071 3 F Update to UE related analytics 16.2.0 2019-12 SP#86 SP-191079 0072 F Clarifications on Supporting Modification of Analytics Subscription 16.2.0 2019-12 SP#86 SP-191079 0076 2 F Removing Editor's note on how to find a PCF instance serving a UE 16.2.0 2019-12 SP#86 SP-191079 0078 2 F User Data Congestion - Removal of Editor's Notes and Description Alignments 16.2.0 2019-12 SP#86 SP-191079 0081 3 F CR to update UE communication 16.2.0 2019-12 SP#86 SP-191079 0084 3 F Correction to Analytics Filter for slice load level analytics 16.2.0 2019-12 SP#86 SP-191079 0087 3 F Clarification on NWDAF-assisted expected UE behavioural analytics 16.2.0 2019-12 SP#86 SP-191079 0088 F Update the correlation information for AMF data and RAN data 16.2.0 2019-12 SP#86 SP-191079 0091 1 F Clarification of UE related analytics 16.2.0 2019-12 SP#86 SP-191079 0092 F Clarification of QoS requirements parameter used for QoS Sustainability Analytics 16.2.0 2019-12 SP#86 SP-191079 0093 4 F Alignments on Analytics Filter Information and clarifications on Reporting Thresholds 16.2.0 2019-12 SP#86 SP-191079 0094 1 F Clarification for UPF related data collection 16.2.0 2019-12 SP#86 SP-191120 0095 3 F Alignment of User Data Congestion Analytics 16.2.0 2019-12 SP#86 SP-191079 0099 1 F NEF parameter mapping for outbound analytics 16.2.0 2019-12 SP#86 SP-191079 0100 5 F Alignments on QoS Sustainability Analytics 16.2.0 2020-03 SP#87E SP-200070 0103 1 F Clarification on definitions and NSI 16.3.0 2020-03 SP#87E SP-200070 0104 - F NWDAF collect MDT/SON parameters 16.3.0 2020-03 SP#87E SP-200070 0105 1 F Update to Clause 6.1.3 Contents of Analytics Exposure 16.3.0 2020-03 SP#87E SP-200070 0108 2 F CR to update Observed Service Experience 16.3.0 2020-03 SP#87E SP-200070 0109 3 F Corrections on UE mobility analytics type by NWDAF service 16.3.0 2020-03 SP#87E SP-200070 0110 3 F Corrections on UE mobility analytics type by NWDAF service 16.3.0 2020-03 SP#87E SP-200070 0112 2 F Correct the filters for UE related analytics 16.3.0 2020-03 SP#87E SP-200070 0113 4 F A mechanism to avoid the flooding of reporting 16.3.0 2020-03 SP#87E SP-200070 0114 1 F Reporting information updates 16.3.0 2020-03 SP#87E SP-200070 0115 1 F Mega CR on editorial corrections 16.3.0 2020-03 SP#87E SP-200070 0117 1 F Slice service experience data collection corrections 16.3.0 2020-03 SP#87E SP-200070 0119 1 F Add the definition for Maximum number of results parameter into clause 6.1.3 16.3.0 2020-03 SP#87E SP-200070 0123 1 F Clarification of clause 6.7.2 UE mobility analytics 16.3.0 2020-03 SP#87E SP-200070 0124 1 F Clarification of clause 6.7.4 Expected UE behavioural parameters related network data analytics 16.3.0 2020-03 SP#87E SP-200070 0126 1 F Clarification on abnormal behaviour analytics 16.3.0 2020-03 SP#87E SP-200070 0127 1 F Clarifications on data collection 16.3.0 2020-03 SP#87E SP-200070 0128 1 F Corrections to Observed Service Experience analytics 16.3.0 2020-03 SP#87E SP-200070 0129 1 F Corrections to User Data Congestion Analytics 16.3.0 2020-03 SP#87E SP-200070 0130 - F Corrections related to Analytics Filter Information and others 16.3.0 2020-03 SP#87E SP-200070 0132 - F Clarifications on Inputs of NWDAF Analytics Subscription 16.3.0 2020-03 SP#87E SP-200070 0139 - F Clarification of data collection from UPF 16.3.0 2020-03 SP#87E SP-200070 0140 - F TS 23.288 editor's note handling 16.3.0 2020-03 SP#87E SP-200070 0142 1 F Clarification on the NWDAF services invoked in Abnormal behaviour 16.3.0 2020-07 SP#88E SP-200431 0118 3 F Abnormal analytics for any UE 16.4.0 2020-07 SP#88E SP-200431 0146 1 F Clarification of NF load analytics procedure 16.4.0 2020-07 SP#88E SP-200431 0148 1 F Clarification on Data Collection Procedure 16.4.0 2020-07 SP#88E SP-200431 0149 1 F Correction on Probability Assertion 16.4.0 2020-07 SP#88E SP-200431 0150 1 F Miscellaneous FASMO corrections to service experience analytics 16.4.0 2020-07 SP#88E SP-200431 0153 1 F Support of abnormal behaviour analytics for any UE 16.4.0 2020-07 SP#88E SP-200431 0154 1 F Support of data collection for any UE 16.4.0 2020-07 SP#88E SP-200431 0155 2 F Clarification on UE mobility analytics exposed to AF 16.4.0 2020-07 SP#88E SP-200431 0156 1 F Abnormal analytics clarifications (not any UE related) 16.4.0 2020-07 SP#88E SP-200431 0158 1 F Clarification on Event and Analytics Filters for some analytics types 16.4.0 2020-07 SP#88E SP-200431 0159 - F The term MoS to apply for all kind of services 16.4.0 2020-07 SP#88E SP-200431 0160 1 F Further corrections to Observed Service Experience analytics 16.4.0 2020-07 SP#88E SP-200431 0161 1 F Clarifications on procedures for analytics exposure 16.4.0 2020-07 SP#88E SP-200431 0162 1 F Clarifications on procedures for data collection 16.4.0 2020-07 SP#88E SP-200431 0163 1 F Further clarifications on abnormal behaviour related network data analytics 16.4.0 2020-07 SP#88E SP-200431 0165 1 F Clarification for the Network Performance analytics 16.4.0 2020-07 SP#88E SP-200431 0166 1 F Updates of data collection for slice service experience 16.4.0 2020-07 SP#88E SP-200431 0167 1 F Corrections related to external UE ID 16.4.0 2020-07 SP#88E SP-200431 0168 - F General clean-up for output abnormal behaviour analytics 16.4.0 2020-07 SP#88E SP-200431 0169 - F Removing service provider actions for exception ID ping-ponging across neighbouring cells 16.4.0 2020-07 SP#88E SP-200431 0170 1 F Updated Event IDs for analytics 16.4.0 2020-07 SP#88E SP-200431 0172 1 F Corrections to Nnwdaf service operations 16.4.0 2020-07 SP#88E SP-200431 0173 1 F Adding UDM and OAM as consumers of services provided by NWDAF 16.4.0 2020-07 SP#88E SP-200431 0176 1 F Corrections for maximum number of objects and Maximum number of SUPIs 16.4.0 2020-09 SP#89E SP-200679 0177 1 F Service experience analytics discrimination 16.5.0 2020-09 SP#89E SP-200679 0178 - F Corrections for wrong references for TS 28.532 clauses 16.5.0 2020-09 SP#89E SP-200679 0179 - F Clarification on Target of Event Reporting 16.5.0 2020-09 SP#89E SP-200679 0181 2 F Clarification on Analytics Exposure 16.5.0 2020-09 SP#89E SP-200679 0182 1 F Clarification on data collection for statistics 16.5.0 2020-09 SP#89E SP-200679 0183 1 F Clarification on mapping of expected analytics type and Exception IDs 16.5.0 2020-09 SP#89E SP-200679 0184 1 F Clarification on NWDAF identifying the AF to collect data for an Event 16.5.0 2020-09 SP#89E SP-200679 0186 1 F Clarification on Multiple Parameter Sets for QoS Sustainability 16.5.0 2020-12 SP#90E SP-200957 0188 1 F Clarifications for Charging function as NWDAF consumer 16.6.0 2021-03 SP#90E SP-210246 0192 - F Correct wrong reference 16.7.0 2021-03 SP#90E SP-210246 0199 1 F UE location in the AMF 16.7.0 2021-03 SP#90E SP-210070 0193 1 B Analytics ID UE communication and Observed Service Experience Extension to Support Application Related Analytics for RFSP Policy 17.0.0 2021-03 SP#90E SP-210070 0194 2 B Dispersion Analytics 17.0.0 2021-03 SP#90E SP-210070 0195 1 B Persistent Data Collection 17.0.0 2021-03 SP#90E SP-210070 0196 1 C Extending Observed Service Experience related network data analytics with cell energy saving state to Support UP path selection enhancement 17.0.0 2021-03 SP#90E SP-210070 0197 1 B Adding a new analytics WLAN performance 17.0.0 2021-03 SP#90E SP-210070 0198 1 B Adding Analytics IDs 17.0.0 2021-03 SP#90E SP-210070 0200 1 B Extensions to User Data Congestion Analytics 17.0.0 2021-03 SP#90E SP-210070 0201 1 C KI#4: Slice load level related network data analytics 17.0.0 2021-03 SP#90E SP-210070 0202 1 C KI#4: Additional consumer NFs for service experience analytics 17.0.0 2021-03 SP#90E SP-210070 0203 1 C Network slice information from OAM 17.0.0 2021-03 SP#90E SP-210070 0204 1 C UE Communication analytics updates for user plane optimization 17.0.0 2021-03 SP#90E SP-210070 0205 1 B NWDAF decomposition 17.0.0 2021-03 SP#90E SP-210070 0206 1 B NWDAF - Data repository function 17.0.0 2021-03 SP#90E SP-210070 0207 1 B Procedure for Multiple NWDAF Analytics aggregation 17.0.0 2021-03 SP#90E SP-210070 0208 1 B Procedure for time coordination across multiple NWDAF instances 17.0.0 2021-03 SP#90E SP-210070 0209 1 B NF Load analytics enhancement 17.0.0 2021-03 SP#90E SP-210070 0210 1 B Session Management Congestion Control Experience Analytics 17.0.0 2021-03 SP#90E SP-210070 0211 1 B Adding the new analytics Redundant Transmission Experience 17.0.0 2021-03 SP#90E SP-210070 0212 1 C Extension of the existing analytics, UE Mobility 17.0.0 2021-03 SP#90E SP-210070 0213 1 B Hierarchical Principles and Interactions on Multiple NWDAFs in TS23.288 17.0.0 2021-03 SP#90E SP-210070 0214 1 B Principles, Procedures, Services of Bulked Data Collection in TS23.288 17.0.0 2021-03 SP#90E SP-210071 0215 1 B Implementation of Support For Discovering and Tracking Entities in Area of Interesting in TS23.288 17.0.0 2021-03 SP#90E SP-210071 0216 1 B Implementation of Enhancements on Event Exposure used by NWDAF in TS23.288 17.0.0 2021-03 SP#90E SP-210071 0218 1 B ML Model sharing between NWDAF instances 17.0.0 2021-03 SP#90E SP-210071 0219 1 B Analytics ID Service Experience Extension to Support UP path selection enhancement 17.0.0 2021-03 SP#90E SP-210071 0220 1 B KI#11: Update of data collection procedures 17.0.0 2021-03 SP#90E SP-210071 0221 1 B KI#1: Extension of functional descriptions for Model training logical function 17.0.0 2021-03 SP#90E SP-210071 0222 1 B KI#19: Procedures for ML Model provisioning and training 17.0.0 2021-03 SP#90E SP-210071 0223 1 B Multiple NWDAF instances architecture 17.0.0 2021-03 SP#90E SP-210071 0224 1 B Procedures for model sharing 17.0.0 2021-03 SP#90E SP-210071 0229 1 B NWDAF discovery for no AOI case 17.0.0 2021-03 SP#90E SP-210071 0230 1 B Support of analytics aggregation without provision of AOI 17.0.0 2021-03 SP#90E SP-210071 0233 1 B Support of DN performance analytics by NWDAF 17.0.0 2021-03 SP#90E SP-210071 0235 1 B DCCF and ADRF architectural changes to increasing efficiency of data collection 17.0.0 2021-03 SP#90E SP-210071 0236 1 B Procedures for data collection using DCCF 17.0.0 2021-03 SP#90E SP-210071 0237 1 B Procedures for data collection using DCCF and Messaging Framework 17.0.0 2021-03 SP#90E SP-210071 0238 - B Procedures for analytics exposure using DCCF 17.0.0 2021-03 SP#90E SP-210071 0239 1 B Procedures for analytics exposure using DCCF and Messaging Framework 17.0.0 2021-03 SP#90E SP-210071 0240 - B NWDAF usage of partitioning criteria 17.0.0 2021-03 SP#90E SP-210071 0241 1 B New procedure for data collection from UE 17.0.0 2021-03 SP#90E SP-210071 0244 1 B Increasing efficiency of data collection (Architecture part) 17.0.0 2021-03 SP#90E SP-210071 0248 1 B Update the procedure for Observed Service Experience related network data analytics case 17.0.0 2021-03 SP#90E SP-210072 0250 1 B Service operations for Multiple NWDAF Analytics aggregation 17.0.0 2021-03 SP#90E SP-210072 0251 1 B NWDAF Reselection for Multiple NWDAF deployments - procedures 17.0.0 2021-03 SP#90E SP-210072 0252 1 B NWDAF Discovery and Selection for Multiple NWDAF 17.0.0 2021-03 SP#90E SP-210072 0255 1 B Improvements on analytics subsets, accuracy levels and ordering of results 17.0.0 2021-03 SP#90E SP-210072 0256 1 B NWDAF Reselection for Multiple NWDAF deployments - service operations 17.0.0 2021-06 SP#92E SP-210348 0243 5 B Exposing UE mobility analytics for multiple NWDAFs case 17.1.0 2021-06 SP#92E SP-210348 0257 1 B KI#7 - Extensions to User Data Congestion Analytics 17.1.0 2021-06 SP#92E SP-210348 0258 3 B KI#8 - Resolving Editors note on mapping UE IP address and SUPI or GPSI 17.1.0 2021-06 SP#92E SP-210348 0259 2 B NWDAF registering into UDM 17.1.0 2021-06 SP#92E SP-210348 0260 2 B Updating clause 5.2 for the discovery of NWDAFs 17.1.0 2021-06 SP#92E SP-210348 0262 2 B CR to update MTLF services to resolve ENs 17.1.0 2021-06 SP#92E SP-210348 0263 1 B CR to resolve ENs related to multiple MTLFs 17.1.0 2021-06 SP#92E SP-210330 0265 1 A Delete NSI ID via N7 interface 17.1.0 2021-06 SP#92E SP-210350 0266 1 F Clarification on DCCF usage in non-roaming architecture 17.1.0 2021-06 SP#92E SP-210350 0267 1 F Clarification on applying analytics subsets 17.1.0 2021-06 SP#92E SP-210348 0268 1 B Adding Application Status to analytics filter information 17.1.0 2021-06 SP#92E SP-210350 0272 1 D Removal of Editorial Note related to Namf/Nsmf_EventExposure 17.1.0 2021-06 SP#92E SP-210348 0273 1 B Preferred granularity of location in analytics outputs 17.1.0 2021-06 SP#92E SP-210348 0274 1 B Alignments on analytics subsets, accuracy levels and ordering of results 17.1.0 2021-06 SP#92E SP-210348 0275 1 B Use of UE behaviour, location and communication trends for analytics optimization 17.1.0 2021-06 SP#92E SP-210348 0276 1 B Service Experience Analytics outputs RAT Type and Frequency information 17.1.0 2021-06 SP#92E SP-210350 0278 - F Removal of analytics consumer or data consumer from the list 17.1.0 2021-06 SP#92E SP-210350 0280 3 F Resolving EN on analytics metadata request 17.1.0 2021-06 SP#92E SP-210350 0282 - F Analytics Context Information Transfer 17.1.0 2021-06 SP#92E SP-210350 0283 1 F Services for Analytics Subscription Transfer 17.1.0 2021-06 SP#92E SP-210348 0285 1 B Removing EN on dataset statistical properties related to analytics aggregation definitions. 17.1.0 2021-06 SP#92E SP-210350 0286 4 F Removing EN on bulked data definitions and procedures. 17.1.0 2021-06 SP#92E SP-210348 0287 1 B Remove ENs from Event Muting Mechanisms 17.1.0 2021-06 SP#92E SP-210348 0288 1 B Removal of FFS on SMF mapping of PDU sessions to TAI 17.1.0 2021-06 SP#92E SP-210348 0289 2 B Removal of EN related to network slice association information in TS 23.288. 17.1.0 2021-06 SP#92E SP-210348 0290 1 B Alignment of NWDAF discovery of data exposure capability in TS 23.288. 17.1.0 2021-06 SP#92E SP-210348 0291 4 B NWDAF discovery and selection based on ML Model information 17.1.0 2021-06 SP#92E SP-210348 0293 4 B Add bandwidth into Dispersion analytics per slice 17.1.0 2021-06 SP#92E SP-210350 0295 1 C Improve the accuracy of the analytics ouput based on Abnormal Behaviour analytics interactions between NWDAFs 17.1.0 2021-06 SP#92E SP-210348 0297 1 B Clarification on MTLF determining when further training is required 17.1.0 2021-06 SP#92E SP-210350 0299 4 F Resolve ENs for clause 6.1A.3.2 17.1.0 2021-06 SP#92E SP-210350 0300 3 F Data collection within AoI for specific UEs 17.1.0 2021-06 SP#92E SP-210350 0304 5 F Miscellaneous correction(s) 17.1.0 2021-06 SP#92E SP-210348 0305 3 B Definition of Nnwdaf_MLModelInfo_Request procedure and services 17.1.0 2021-06 SP#92E SP-210348 0306 2 B ADRF functional description 17.1.0 2021-06 SP#92E SP-210348 0307 - B Editor's note resolution for data and analytics collection via messaging framework 17.1.0 2021-06 SP#92E SP-210573 0308 4 B DCCF services definition 17.1.0 2021-06 SP#92E SP-210349 0309 - B MFAF services definition 17.1.0 2021-06 SP#92E SP-210349 0310 1 B Data collection profile parameters 17.1.0 2021-06 SP#92E SP-210349 0311 1 B Clarify the procedure for exposing Service Experience to a MEC 17.1.0 2021-06 SP#92E SP-210349 0315 1 B Update the procedure for Data Collection from NWDAF 17.1.0 2021-06 SP#92E SP-210349 0318 4 B Update to NF Load Analytics 17.1.0 2021-06 SP#92E SP-210349 0319 1 B Update to time coordination across multiple NWDAF instances 17.1.0 2021-06 SP#92E SP-210350 0320 - C Correlation ID for transfer of analytics subscription 17.1.0 2021-06 SP#92E SP-210349 0322 1 B Analytics aggregation - EN resolutions 17.1.0 2021-06 SP#92E SP-210349 0323 - B Analytics aggregation - analytics metadata provisioning 17.1.0 2021-06 SP#92E SP-210349 0324 1 B Analytics aggregation - analytics metadata content 17.1.0 2021-06 SP#92E SP-210349 0326 3 B User Data congestion analytics update 17.1.0 2021-06 SP#92E SP-210349 0329 - B Analytics transfer service operations 17.1.0 2021-06 SP#92E SP-210349 0330 3 B Extension of Naf_EventExposure for observed service experience data collection from UEs 17.1.0 2021-06 SP#92E SP-210333 0334 1 A Clarification on output parameters in OSE 17.1.0 2021-06 SP#92E SP-210349 0336 1 B Data collection from UE Application 17.1.0 2021-06 SP#92E SP-210349 0337 1 B Mapping UE IP address and GPSI 17.1.0 2021-06 SP#92E SP-210349 0338 1 B User consent to data collection and analytics 17.1.0 2021-06 SP#92E SP-210350 0341 1 F Adding clarifications related to the Supported Analytic Delay 17.1.0 2021-06 SP#92E SP-210349 0342 - B Dispersion Analytics and DN Performance Analytics to Table 7.1-2 17.1.0 2021-06 SP#92E SP-210349 0343 1 B Addition of sets of NWDAF identifiers involved in analytics aggregation 17.1.0 2021-06 SP#92E SP-210350 0348 1 F Update to slice load analytics procedure 17.1.0 2021-06 SP#92E SP-210349 0351 1 B Removal of FFS Clause 6.2.2.1 on determining data sources in area of interest 17.1.0 2021-06 SP#92E SP-210350 0352 1 F Clarification on data storage in ADRF 17.1.0 2021-06 SP#92E SP-210350 0353 1 F Analytics Subscription Transfer for aggregator NWDAF 17.1.0 2021-06 SP#92E SP-210349 0355 1 B Clarification on the NWDAF decomposition 17.1.0 2021-06 SP#92E SP-210349 0356 1 B Analytics request to collect data from UE for any UE 17.1.0 2021-06 SP#92E SP-210349 0359 - B Update to Contents of Analytics Exposure 17.1.0 2021-06 SP#92E SP-210349 0360 1 B Update to NF Load Analytics Output data 17.1.0 2021-06 SP#92E SP-210349 0361 1 B Update to UE Data Collection 17.1.0 2021-06 SP#92E SP-210349 0362 1 B ML Model Provisioning filter information 17.1.0 2021-06 SP#92E SP-210350 0363 1 F Clarification of Application Server address within Analytics Filter information in DN Performance Analytics 17.1.0 2021-06 SP#92E SP-210350 0364 1 F Clarification of Application Server address within Analytics Filter information in Service Experience Analytics 17.1.0 2021-06 SP#92E SP-210350 0366 1 F Correction to UE communication analytics for PDU session inactivity timer 17.1.0 2021-06 SP#92E SP-210350 0368 1 F Dispersion analytics update 17.1.0 2021-06 SP#92E SP-210349 0369 1 B Processing and Processing Instructions 17.1.0 2021-06 SP#92E SP-210350 0370 1 B Analytics Data Repository procedures and Historical Data Handling procedure 17.1.0 2021-06 SP#92E SP-210350 0371 - B Procedure for data removal from ADRF 17.1.0 2021-06 SP#92E SP-210350 0372 - F Alignment with ADRF functional description and ADRF service operations 17.1.0 2021-06 SP#92E SP-210350 0374 1 B Procedure for Historical Data and Analytics Storage via Notifications 17.1.0 2021-09 SP#93E SP-210921 0377 1 F Resolving editor's notes for references to NWDAF services and cleanup for call flows 17.2.0 2021-09 SP#93E SP-210921 0378 - F DCCF for data collection from applications in the UE 17.2.0 2021-09 SP#93E SP-210921 0379 1 F ADRF ID in Nmfaf_3daDataManagement_Configure service operation 17.2.0 2021-09 SP#93E SP-210922 0381 1 B KI#15 - User consent 17.2.0 2021-09 SP#93E SP-210921 0382 1 B Collection of input data for Analytics ID Load level information 17.2.0 2021-09 SP#93E SP-210921 0383 1 C Defines the Analytics Context identifiers 17.2.0 2021-09 SP#93E SP-210921 0384 1 C Updates to Analytics Context information 17.2.0 2021-09 SP#93E SP-210921 0385 1 C Updates for Analytics Context Information Transfer 17.2.0 2021-09 SP#93E SP-210921 0386 1 F NWDAF procedures for Analytics transfer update 17.2.0 2021-09 SP#93E SP-210921 0387 1 B NWDAF selection including transfer of Analytics context 17.2.0 2021-09 SP#93E SP-210921 0388 1 C NWDAF re-selection for Multiple NWDAF deployments - procedures -update 17.2.0 2021-09 SP#93E SP-210921 0389 1 F Data collection from AF support for internal group ID 17.2.0 2021-09 SP#93E SP-210921 0390 - F Editorial fix in clause 5.2 17.2.0 2021-09 SP#93E SP-210921 0393 - C Update to Suspicion of DDoS attack 17.2.0 2021-09 SP#93E SP-210921 0394 1 C Application ID - an optional input in Dispersion Analytics 17.2.0 2021-09 SP#93E SP-210921 0395 - F Correction to reference descriptions for slice load level analytics 17.2.0 2021-09 SP#93E SP-210921 0396 - B Removing EN on Frequency in OSE 17.2.0 2021-09 SP#93E SP-210907 0398 1 A Clarify the data source of UE behavioural information and expected UE behavioural parameters 17.2.0 2021-09 SP#93E SP-210921 0400 F Remove the FFS on how to remove the noise data by the abnormal UE list 17.2.0 2021-09 SP#93E SP-210921 0401 1 F Alignment of the ML Model subscription and ML Model request 17.2.0 2021-09 SP#93E SP-210921 0404 1 F Clarify the Analytics Filter Information of the ML Model provisioning 17.2.0 2021-09 SP#93E SP-210921 0406 1 F Update to analytics summary table 17.2.0 2021-09 SP#93E SP-210922 0407 1 F Correction for slice restrictions information 17.2.0 2021-09 SP#93E SP-210921 0409 1 F Correction to Annex A reference 17.2.0 2021-09 SP#93E SP-210921 0410 1 F Resolve EN on how the level of accuracy can be derived for analytics reports 17.2.0 2021-09 SP#93E SP-210921 0411 1 F Correction to NWDAF Data management service operation 17.2.0 2021-09 SP#93E SP-210921 0412 - F Correction in General description of DN Performance Analytics 17.2.0 2021-09 SP#93E SP-210921 0414 1 F Corrections and clarifications related to analytics subscription transfer 17.2.0 2021-09 SP#93E SP-210921 0417 1 F Corrections related to analytics aggregation 17.2.0 2021-09 SP#93E SP-210921 0421 1 F Clarification on the usage of Supported Analytics Delay when the NWDAF also supports Analytics Aggregation 17.2.0 2021-09 SP#93E SP-210922 0424 - F Clarification on Analytics Subscription Transfer 17.2.0 2021-09 SP#93E SP-210922 0426 1 F Mapping information update in UE data collection procedure 17.2.0 2021-09 SP#93E SP-210922 0427 2 F Miscellaneous correction for TS 23.288 17.2.0 2021-09 SP#93E SP-210922 0428 1 F Update description for AF registration to the NRF in TS 23.288 17.2.0 2021-09 SP#93E SP-210922 0429 1 F Clarifying that some data types for a specific UE collected from OAM via MDT 17.2.0 2021-09 SP#93E SP-210922 0430 2 F Clarify and complement the data source for data collection for NWDAF containing MTLF 17.2.0 2021-09 SP#93E SP-210922 0431 1 F Clarification about the Application ID in the NF profile for AF registration to the NRF 17.2.0 2021-09 SP#93E SP-210922 0432 1 F ML Model storage alignment 17.2.0 2021-09 SP#93E SP-210922 0433 - F Clarification on the NWDAF or AF triggered mapping procedure 17.2.0 2021-09 SP#93E SP-210922 0434 1 F Removal of EASDF 17.2.0 2021-12 SP#94E SP-211292 0437 1 F Add mute to DataManagement service 17.3.0 2021-12 SP#94E SP-211292 0438 1 F Correcting inconsistencies for analytics transfer 17.3.0 2021-12 SP#94E SP-211292 0439 1 F UDM-based discovery of NWDAF in Analytics Aggregation procedure 17.3.0 2021-12 SP#94E SP-211292 0441 - F Alignment of NWDAF services Example Consumers with corresponding procedures 17.3.0 2021-12 SP#94E SP-211292 0443 1 F Clarify the OSE analytics per RAT type and/or per Frequency 17.3.0 2021-12 SP#94E SP-211292 0444 1 F Alignment and corrections related to accuracy, confidence and normative wording in notes 17.3.0 2021-12 SP#94E SP-211292 0445 1 F Alignment, clarifications, corrections related to KI#2 and KI#11 17.3.0 2021-12 SP#94E SP-211292 0447 1 F Clarification for Supported Analytics Delay when reporting mode is requested 17.3.0 2021-12 SP#94E SP-211292 0449 1 F Clarify the Analytics target period 17.3.0 2021-12 SP#94E SP-211292 0450 3 F Clarify the content of ML Model provisioning 17.3.0 2021-12 SP#94E SP-211292 0451 1 F Clarify the Slice load level analytics 17.3.0 2021-12 SP#94E SP-211292 0453 2 F Clarification on Per-UE Service Experience Request Procedure 17.3.0 2021-12 SP#94E SP-211293 0455 3 F Restriction for 5GC to provide UE IP address to untrusted AF 17.3.0 2021-12 SP#94E SP-211292 0456 1 F Update on Analytics context transfer and clarification on Termination Request 17.3.0 2021-12 SP#94E SP-211292 0457 1 F Clarifications on transfer of analytics context and analytics subscription 17.3.0 2021-12 SP#94E SP-211292 0458 1 F Clarifications on prepared analytics transfer 17.3.0 2021-12 SP#94E SP-211292 0459 1 F Clarifications on analytics aggregation 17.3.0 2021-12 SP#94E SP-211292 0461 1 F Clarify the NWDAF (MTLF) and NWDAF (AnLF) 17.3.0 2021-12 SP#94E SP-211292 0463 3 F Clarify the UE aggregated mobility analytics exposure to NF 17.3.0 2021-12 SP#94E SP-211292 0464 - F Content correction of user consent 17.3.0 2021-12 SP#94E SP-211292 0465 1 F Clean up for UE data reporting procedure 17.3.0 2021-12 SP#94E SP-211292 0467 3 F Miscellaneous corrections for TS 23.288 on eNA_ph2 17.3.0 2021-12 SP#94E SP-211292 0468 1 F Clarification for analytics exposure via NWDAF(hosting DCCF) 17.3.0 2021-12 SP#94E SP-211292 0469 1 F Clarification for analytics subscription termination request 17.3.0 2021-12 SP#94E SP-211293 0471 1 F Correction on NWDAF reselectioin 17.3.0 2021-12 SP#94E SP-211275 0474 1 A Add the description of Wrong destination address 17.3.0 2021-12 SP#94E SP-211293 0475 1 F Clarifications for Ndccf services and Nnwdaf_DataManagement services 17.3.0 2021-12 SP#94E SP-211293 0476 1 F Clarify the resource usage for a network slice instance 17.3.0 2021-12 SP#94E SP-211293 0478 1 F Clarification on external triggers and clean up the UE mobility analytics 17.3.0 2021-12 SP#94E SP-211293 0479 1 F Clarifications for UE data collection 17.3.0 2021-12 SP#94E SP-211293 0480 1 F User consent for analytics and model training 17.3.0 2021-12 SP#94E SP-211293 0481 1 F Term alignment of Target of Analytics Reporting and Analytics Filter Information 17.3.0 2021-12 SP#94E SP-211293 0482 1 F Adding a list to enumerate NF services for enhanced procedures data collection 17.3.0 2021-12 SP#94E SP-211293 0484 1 F Termination request or rejection of NWDAF data managment service due to user consent not granted 17.3.0 2021-12 SP#94E SP-211293 0486 1 F Corrections to discovery for NWDAF containing MTLF 17.3.0 2021-12 SP#94E SP-211293 0490 1 F Alignment and corrections related to prepared analytics transfer 17.3.0 2021-12 SP#94E SP-211293 0491 1 F Clarification on interaction between timers and supported analytics Delay 17.3.0 2021-12 SP#94E SP-211293 0492 1 F Resolve normative wording in notes 17.3.0 2021-12 SP#94E SP-211293 0493 1 B DCCF-based user consent checking 17.3.0 2022-03 SP#95E SP-220056 0425 2 F Update of Data collection from OAM 17.4.0 2022-03 SP#95E SP-220056 0489 2 F Clarification on including location information for OSE analytics 17.4.0 2022-03 SP#95E SP-220056 0494 1 F ADRF ID in the analytics context between NWDAFs 17.4.0 2022-03 SP#95E SP-220056 0496 - F Correction for the figure of DN Performance Analytics 17.4.0 2022-03 SP#95E SP-220056 0497 1 F Clarification on Dispersion Analytic for identification of Top-Heavy UEs in a location 17.4.0 2022-03 SP#95E SP-220056 0499 1 F Clarification on identifiers used as Target of Analytics Reporting 17.4.0 2022-03 SP#95E SP-220056 0500 1 F Correction on Analytics ID on Service Experience 17.4.0 2022-03 SP#95E SP-220056 0504 1 F Clarification for Analytics Aggregation without Provision of Area of Interest 17.4.0 2022-03 SP#95E SP-220056 0505 1 F Update for the user consent checking 17.4.0 2022-03 SP#95E SP-220056 0506 1 F Remove the redundant content of performance data collected from SMF 17.4.0 2022-03 SP#95E SP-220056 0507 - F Remove the statistics value or expected value for load level 17.4.0 2022-03 SP#95E SP-220056 0508 1 F Clarification on UE related analytics 17.4.0 2022-03 SP#95E SP-220056 0509 1 F Correction on service operation to retreive the number of UE and number of PDU session 17.4.0 2022-06 SP#96 SP-220399 0462 4 F Clarify the Redundant Transmission Experience related analytics 17.5.0 2022-06 SP#96 SP-220399 0488 3 F Clarification of transferring ML Model during analytics transfer 17.5.0 2022-06 SP#96 SP-220399 0510 1 F Clarification on historical data and analytics storage via MFAF 17.5.0 2022-06 SP#96 SP-220399 0511 1 F Alignment and corrections on analytics subscription procedures 17.5.0 2022-06 SP#96 SP-220399 0512 1 F Inputs update for NWDAF Notify services for missing elements 17.5.0 2022-06 SP#96 SP-220399 0513 1 F Correction to Dispersion Analytics 17.5.0 2022-06 SP#96 SP-220399 0515 1 F Alignment on the data collection from NSACF 17.5.0 2022-06 SP#96 SP-220399 0517 1 F Clarify the Analytics subset per different Analytics ID 17.5.0 2022-06 SP#96 SP-220399 0518 - F Adding UE ID to the Service Data from AF related to the Observed Service Experience 17.5.0 2022-06 SP#96 SP-220399 0519 1 F Update inputs parameters for the Nadrf_DataManagement_StorageRequest service 17.5.0 2022-06 SP#96 SP-220399 0520 1 F Clarification on data collection with Event Muting Mechanism 17.5.0 2022-06 SP#96 SP-220391 0527 - A Removing UDM as consumer of expected UE behavioural parameters analytics 17.5.0 2022-06 SP#96 SP-220399 0528 1 F Update the Slice Load Level Analytics and DN Performance Analytics 17.5.0 2022-09 SP#97E SP-220778 0532 1 F Clarification to Data Delivery and Data Collection via DCCF and via MFAF 17.6.0 2022-09 SP#97E SP-220778 0533 1 F Clarification on granularity of time and location for NWDAF analytics results 17.6.0 2022-09 SP#97E SP-220770 0535 1 A Correction for packet retransmission input for service experience analytics 17.6.0 2022-09 SP#97E SP-220778 0536 - D Correction on wrong reference clause number 17.6.0 2022-09 SP#97E SP-220778 0537 1 F Alignment of DCCF and NWDAF Data Management services and corrections to ADRF Data Management service 17.6.0 2022-09 SP#97E SP-220778 0538 1 F Corrections on information of previous analytics subscription 17.6.0 2022-09 SP#97E SP-220778 0539 1 F Correction of wrong references to TS28.532 17.6.0 2022-09 SP#97E SP-220778 0540 1 F Clarify the Nadrf_DataManagement_RetrievalRequest service 17.6.0 2022-12 SP#98E SP-221070 0546 - F Corrections to Slice Load level Analytics ID 17.7.0 2022-12 SP#98E SP-221070 0547 - F Remove the Editor's Note related to EVEX in SA4 17.7.0 2022-12 SP#98E SP-221070 0550 1 F Formatting and Processing Instructions related correction to Nadrf_DataManagement service 17.7.0 2022-12 SP#98E SP-221070 0552 - F Corrections for time window in ADRF Nadrf_DataManagement service 17.7.0 2022-12 SP#98E SP-221070 0553 1 F Corrections on exposing 5GS information to untrusted AF 17.7.0 2022-12 SP#98E SP-221255 0596 - F Correction on SMCCE Analytics 17.7.0 2022-12 SP#98E SP-221093 0551 1 B Alignment for UPF event exposure service to NWDAF via the SMF in TS 23.288 18.0.0 2022-12 SP#98E SP-221096 0554 1 B TS 23.288 Enhancement to Support AI/ML Data Transfer 18.0.0 2022-12 SP#98E SP-221139 0558 3 B Adding Interoperability Indicator for ML Model sharing 18.0.0 2022-12 SP#98E SP-221139 0559 2 B Multiple ML Models for an analytics ID 18.0.0 2022-12 SP#98E SP-221139 0561 1 B Use case context 18.0.0 2022-12 SP#98E SP-221139 0565 1 B Improving the Correctness of Service Experience Predictions with Contribution Weights 18.0.0 2022-12 SP#98E SP-221096 0566 2 B Enhancements to Network Performance Analytics to support AIML data traffic policies 18.0.0 2022-12 SP#98E SP-221139 0569 - B Enhancement on OSE for NWDAF assisting PCF in making URSP decisions 18.0.0 2022-12 SP#98E SP-221096 0575 2 B NWDAF updates to assist resource monitoring of AI/ML-based services 18.0.0 2022-12 SP#98E SP-221139 0576 2 B QoS sustainability analytics enhancement 18.0.0 2022-12 SP#98E SP-221139 0582 5 B Federated Learning among Multiple NWDAFs in TS 23.288 18.0.0 2022-12 SP#98E SP-221139 0584 3 B NWDAF-assisted application detection in TS 23.288 18.0.0 2022-12 SP#98E SP-221139 0595 1 B Update TS23.288 to Manage Event Muting Impact on NFp 18.0.0 2023-03 SP#99 SP-230054 0555 5 B Updates for DN performance Analytics of Group UEs 18.1.0 2023-03 SP#99 SP-230060 0556 2 B Updates for Model Provisioning for Analytics of Group UEs 18.1.0 2023-03 SP#99 SP-230060 0557 7 B Monitoring of accuracy of ML Models 18.1.0 2023-03 SP#99 SP-230060 0564 4 B Adding Accuracy Checking Capability to NWDAF Architecture 18.1.0 2023-03 SP#99 SP-230060 0592 2 B Enhancing location analytics with finer granularity location information 18.1.0 2023-03 SP#99 SP-230060 0602 1 F Update ML Model provisioning service with Interoperability Information 18.1.0 2023-03 SP#99 SP-230060 0604 7 B Support the Maintenance of Federated Learning Process in 5GC 18.1.0 2023-03 SP#99 SP-230060 0606 1 B Updates on pending notifications handling 18.1.0 2023-03 SP#99 SP-230054 0608 - B Network performance analytics 18.1.0 2023-03 SP#99 SP-230060 0609 - B Service Experience Analytics ID 18.1.0 2023-03 SP#99 SP-230060 0611 1 B Key Issue #3: Data and analytics exchange in roaming case 18.1.0 2023-03 SP#99 SP-230060 0612 1 B Key Issue #9: Analytic ID that supports location accuracy estimate 18.1.0 2023-03 SP#99 SP-230039 0614 1 A Corrections for historical analytics collection 18.1.0 2023-03 SP#99 SP-230054 0616 6 B KI#7 - 23.288 CR for adding UE Transmission Latency Performance Analytics 18.1.0 2023-03 SP#99 SP-230054 0622 1 F Clarification on enhanced Network Performance analytics 18.1.0 2023-03 SP#99 SP-230060 0625 6 B KI#2 Clarification on PFD Determination Analytics in TS 23.288 18.1.0 2023-03 SP#99 SP-230060 0627 1 B KI#10 NWDAF interaction with MDAS/MDAF in TS 23.288 18.1.0 2023-03 SP#99 SP-230060 0628 11 C Update for Federated Learning among Multiple NWDAFs in TS 23.288 18.1.0 2023-03 SP#99 SP-230060 0630 4 B eNA_Ph3 DCCF relocation in TS 23.288 18.1.0 2023-03 SP#99 SP-230060 0631 8 B QoS sustainability analytics with fine granularity enhancement 18.1.0 2023-03 SP#99 SP-230060 0633 2 B Enhancements on QoS Sustainability analytics 18.1.0 2023-03 SP#99 SP-230060 0634 4 B Enhance NWDAF to enable Federated Learning 18.1.0 2023-03 SP#99 SP-230060 0635 1 B TS 23.288 enhancements for model sharing. 18.1.0 2023-03 SP#99 SP-230060 0636 1 B Roaming architecture for data or analytics exchange 18.1.0 2023-03 SP#99 SP-230060 0637 7 B Analytics/ML Model Accuracy Monitoring Functional Description 18.1.0 2023-03 SP#99 SP-230060 0640 1 B Update on Multiple ML Models for an analytics ID 18.1.0 2023-03 SP#99 SP-230061 0641 8 B ML Model storage and retrieval via ADRF 18.1.0 2023-03 SP#99 SP-230061 0645 3 B KI#4 Optimization on the collection and reporting of network data 18.1.0 2023-03 SP#99 SP-230061 0646 1 B NWDAF data collection from LCS system 18.1.0 2023-03 SP#99 SP-230061 0647 1 B Enhancements to Analytics Reporting Information and NWDAF output 18.1.0 2023-03 SP#99 SP-230061 0651 5 B Relative Proximity Analytics 18.1.0 2023-03 SP#99 SP-230061 0653 1 B UE Mobility analytics enhancement 18.1.0 2023-03 SP#99 SP-230061 0658 4 B KI#1: Update for supporting analytics feedback 18.1.0 2023-03 SP#99 SP-230065 0665 3 B NWDAF analytics to detect URSP enforcement 18.1.0 2023-03 SP#99 SP-230061 0666 3 B NWDAF discovery and selection for an NWDAF supporting MTLF with FL capability 18.1.0 2023-03 SP#99 SP-230061 0669 - C Optimizing data collection and storage by NWDAF registration in UDM for all Analytics IDs 18.1.0 2023-03 SP#99 SP-230054 0671 1 B Enhancement of Service Experience Analytics to assist federated learning operation 18.1.0 2023-03 SP#99 SP-230061 0673 1 B Procedure for accuracy monitoring at NWDAF containing AnLF 18.1.0 2023-03 SP#99 SP-230061 0675 3 B New NWDAF service supporting for AnLF assisted MTLF in accuracy monitoring 18.1.0 2023-03 SP#99 SP-230054 0677 1 B KI#7 23.288 CR for UE mobility analytics to assist FL operation 18.1.0 2023-03 SP#99 SP-230061 0683 1 B Procedures for network data analytics in roaming 18.1.0 2023-03 SP#99 SP-230061 0689 8 B MTLF-based ML Model Accuracy Monitoring 18.1.0 2023-03 SP#99 SP-230061 0690 0 C Data storage in ADRF using DataSetTag. 18.1.0 2023-03 SP#99 SP-230061 0693 1 C Data Storage Management 18.1.0 2023-03 SP#99 SP-230039 0695 - A Corrections to Data Delivery and Data Collection via DCCF and via MFAF 18.1.0 2023-03 SP#99 SP-230039 0696 1 A Corrections on immediate notification in subscription response 18.1.0 2023-03 SP#99 SP-230039 0697 1 A Corrections for historical analytics exposure procedures 18.1.0 2023-03 SP#99 SP-230054 0699 2 B Enhance WLAN performance analytics for Federated Learing member selection 18.1.0 2023-03 SP#99 SP-230061 0704 2 B Add new parameters to Redundant Transmission Experience analytics 18.1.0 2023-03 SP#99 SP-230061 0705 2 B Updates on pending notifications handling by NWDAF 18.1.0 2023-03 SP#99 SP-230061 0706 2 B Support Model Information Exchange for Federated Learning in 5GC 18.1.0 2023-03 SP#99 SP-230061 0707 1 C Update for ML Model provisioning with model identifier 18.1.0 2023-03 SP#99 SP-230061 0714 2 C Updates to FL procedure related to the maximum response time 18.1.0 2023-03 SP#99 SP-230062 0721 3 B Procedure to retrieve ML Model from ADRF 18.1.0 2023-06 SP#100 SP-230467 0598 5 B Rating untrusted AF data sources 18.2.0 2023-05 SP#100 SP-230466 0660 1 A Correction for NEF service for correlating UE data collection and NWDAF request 18.2.0 2023-05 SP#100 SP-230467 0662 8 B New analytics ID for traffic flow use case 18.2.0 2023-05 SP#100 SP-230490 0668 3 F NWDAF discovery with overlapping Serving Areas 18.2.0 2023-05 SP#100 SP-230495 0688 2 C NWDAF access to UPF information 18.2.0 2023-05 SP#100 SP-230467 0702 4 B Adding Data Source Information in the Contents of ML Model Provisioning 18.2.0 2023-05 SP#100 SP-230467 0703 2 C Update for UE mobility analytics using fine granularity in TS 23.288 18.2.0 2023-05 SP#100 SP-230467 0713 4 B Enhancements to analytics specific procedures for analytics exchange in roaming case 18.2.0 2023-05 SP#100 SP-230467 0725 1 B Enhancement of NWDAF with finer granularity of location information in Observed Service Experience Analytic ID 18.2.0 2023-05 SP#100 SP-230467 0726 2 C Data Storage Management 18.2.0 2023-05 SP#100 SP-230467 0727 2 C Data storage in ADRF using DSC indicator 18.2.0 2023-05 SP#100 SP-230476 0728 5 B KI#2- Removing Editors Note 18.2.0 2023-05 SP#100 SP-230467 0729 1 C Update to ML Model storage and retrieval via ADRF 18.2.0 2023-05 SP#100 SP-230467 0730 - B Resolving ENs in AnLF assisted ML Model accuracy monitoring 18.2.0 2023-05 SP#100 SP-230467 0732 1 F Solving EN in the Procedure for Maintaining Federated Learning 18.2.0 2023-05 SP#100 SP-230457 0734 - F Update to the Input of E2E Data Volumn Transfer Time Analytics 18.2.0 2023-05 SP#100 SP-230457 0736 1 C OAM input Corrections and EN addition 18.2.0 2023-05 SP#100 SP-230467 0737 1 C Timestamp of action taken by analytics consumer 18.2.0 2023-05 SP#100 SP-230467 0742 6 B Addressing ENs in location analytics with finer granularity location information 18.2.0 2023-05 SP#100 SP-230467 0743 7 B Addressing ENs on location accuracy analytics 18.2.0 2023-05 SP#100 SP-230457 0748 1 B Service data from AF for E2E data volume transfer time analytics 18.2.0 2023-05 SP#100 SP-230457 0751 1 B Resolve an EN on Which AF event can be used to collect Server location 18.2.0 2023-05 SP#100 SP-230467 0753 - B Update NWDAF Services and analytics information tables for KI#9 18.2.0 2023-05 SP#100 SP-230467 0754 4 B Clarification on data collection frequency mode in TS 23.288 18.2.0 2023-05 SP#100 SP-230467 0755 8 C Clarification on Federated Learning among Multiple NWDAFs in TS 23.288 18.2.0 2023-05 SP#100 SP-230467 0761 3 B Extending Analytics Transfer to support also accuracy checking transfer to target NWDAF. 18.2.0 2023-05 SP#100 SP-230467 0763 5 B Removing Ens from AnLF Analytics Accuracy Monitoring 18.2.0 2023-05 SP#100 SP-230467 0765 8 C Service operations update to general procedure for Federated Learning between NWDAFs 18.2.0 2023-05 SP#100 SP-230467 0767 4 C New parameter introduced in Contents of ML Model Provisioning 18.2.0 2023-05 SP#100 SP-230467 0768 1 C Update to MTLF-based ML Model Accuracy Monitoring Procedure 18.2.0 2023-05 SP#100 SP-230467 0769 3 C General clause update for ML Model(s) retireval from ADRF 18.2.0 2023-05 SP#100 SP-230468 0770 7 B Resolving editor's notes in procedures for analytics exposure in roaming case 18.2.0 2023-05 SP#100 SP-230468 0771 5 C Clarifications to Model storage and retrieval from ADRF 18.2.0 2023-05 SP#100 SP-230468 0773 7 C Updates for Nnwdaf_MLModelTraining service 18.2.0 2023-05 SP#100 SP-230468 0775 1 C Roaming architecture for data or analytics exchange 18.2.0 2023-05 SP#100 SP-230457 0776 1 F AIMLsys: KI#7 - Clarification for validity conditions of E2E data volume transfer time analytics 18.2.0 2023-05 SP#100 SP-230457 0780 1 B Clarification of N6 data collection and output enhancement for End-to-end data volume transfer 18.2.0 2023-05 SP#100 SP-230468 0782 7 B KI#1 Clarification on the accuracy information 18.2.0 2023-06 SP#100 SP-230468 0783 1 B KI#1 Adding the number of inferences for calculating global accuracy 18.2.0 2023-06 SP#100 SP-230466 0785 1 A Clarification for anonymization rules 18.2.0 2023-06 SP#100 SP-230468 0787 5 B KI#1: Update of MLModelMonitor service to deliver Analytics feedback information 18.2.0 2023-06 SP#100 SP-230457 0789 1 F Update to remove the EN for DN performance predictions 18.2.0 2023-06 SP#100 SP-230457 0790 1 F Update the End-to-end data volume transfer time analytics 18.2.0 2023-06 SP#100 SP-230466 0792 - A Clarifications on the Validity period 18.2.0 2023-06 SP#100 SP-230468 0794 3 B Update the procedures for data exchange in roaming case 18.2.0 2023-06 SP#100 SP-230468 0796 - C Update information used for ML Model Accuracy Monitoring 18.2.0 2023-06 SP#100 SP-230468 0800 1 C UE Mobility analytics enhancement 18.2.0 2023-06 SP#100 SP-230468 0801 3 B Procedure for analytics collection from MDAF 18.2.0 2023-06 SP#100 SP-230468 0802 1 B Update the contents of ML Model provisioning 18.2.0 2023-06 SP#100 SP-230468 0807 1 B Enhancement of DN Performance Analytics 18.2.0 2023-06 SP#100 SP-230468 0808 4 B Update of Procedures for Federated Learning 18.2.0 2023-06 SP#100 SP-230468 0816 5 B Resolving Open issues for key issue 3 18.2.0 2023-06 SP#100 SP-230468 0817 1 C Subsets and order of results for newly defined analytics output 18.2.0 2023-06 SP#100 SP-230457 0821 3 B NEF consumes analytic of OSE to support UE member selection 18.2.0 2023-06 SP#100 SP-230468 0822 2 C KI#1 Removing ENs in clause 6.1.3 and 6.2E.2 18.2.0 2023-06 SP#100 SP-230468 0823 4 C General description update about FL 18.2.0 2023-06 SP#100 SP-230468 0826 3 F PFD determination Analytics - Confidence level 18.2.0 2023-06 SP#100 SP-230468 0827 4 B Geographical Identifier in UE Mobility analytics 18.2.0 2023-06 SP#100 SP-230468 0830 2 B Service definitions to support analytics and data exchange for roaming cases 18.2.0 2023-06 SP#100 SP-230468 0832 1 C Update PFD information 18.2.0 2023-06 SP#100 SP-230469 0835 2 C Update the Qos sustainability analytics 18.2.0 2023-06 SP#100 SP-230469 0836 2 C Update the data collection from LCS system 18.2.0 2023-06 SP#100 SP-230469 0839 1 F Update Analytics/ML Model Accuracy Monitoring Functional Description 18.2.0 2023-06 SP#100 SP-230469 0843 2 B Update on NWDAF-assisted URSP 18.2.0 2023-09 SP#101 SP-230847 0852 - F Clarification on enhanced OSE analytics 18.3.0 2023-09 SP#101 SP-230847 0853 1 F Unifying NWDAF roaming exchange terminology and removing EN of the roaming architecture 18.3.0 2023-09 SP#101 SP-230847 0854 1 F Resolving issues in ADRF ML Model Storage services 18.3.0 2023-09 SP#101 SP-230847 0857 - F Number of Inferences in Nnwdaf_MLModelMonitor_Notify service operation 18.3.0 2023-09 SP#101 SP-230847 0862 1 F Corrections to Analytics Subset 18.3.0 2023-09 SP#101 SP-230847 0865 2 F Resolving EN on analytics and data exchange in roaming scenario 18.3.0 2023-09 SP#101 SP-230847 0868 1 F Clarifications on determining accuracy of analytics 18.3.0 2023-09 SP#101 SP-230847 0871 1 F Analytics Transfer Impact in ML Model Accuracy Consumption by NWDAF containing MTLF 18.3.0 2023-09 SP#101 SP-230847 0872 1 F Update the DataSetTag in procedure of MTLF-based ML Model Accuracy Monitoring 18.3.0 2023-09 SP#101 SP-230847 0874 - F Update to procedure for Rating untrusted AF data sources 18.3.0 2023-09 SP#101 SP-230847 0876 - F Correction to ML Model Accuracy information support 18.3.0 2023-09 SP#101 SP-230847 0877 - F Correction to MLModelManagement_Delete service operation 18.3.0 2023-09 SP#101 SP-230847 0878 2 F Clarification for roaming exchange capability 18.3.0 2023-09 SP#101 SP-230847 0879 2 F Modification for ADRF ML Model storage and retrieval 18.3.0 2023-09 SP#101 SP-230847 0880 2 F Refinement for ML Model information for KI#4 18.3.0 2023-09 SP#101 SP-230847 0885 1 F Corrections on AnLF-assisted MTLF monitoring procedure 18.3.0 2023-09 SP#101 SP-230847 0886 - F Corrections on MTLF based ML Model Monitoring 18.3.0 2023-09 SP#101 SP-230847 0894 1 F Update the description about Data collection profile registration 18.3.0 2023-09 SP#101 SP-230847 0895 - F Update the general description of ADRF 18.3.0 2023-09 SP#101 SP-230847 0898 - F Remove EN in Network Performance analytics 18.3.0 2023-09 SP#101 SP-230847 0899 1 F Editorial changes of the parameter used for AnLF Analytics Accuracy Monitoring 18.3.0 2023-09 SP#101 SP-230847 0905 1 F Clarification on ML Model interoperability 18.3.0 2023-09 SP#101 SP-230847 0909 2 F Clarification on multiple ML Models provisioning 18.3.0 2023-12 SP#102 SP-231257 0855 2 F Clarification of federated learning procedure 18.4.0 2023-12 SP#102 SP-231257 0869 5 F Alignment on terminology on obtaining location data from LCS 18.4.0 2023-12 SP#102 SP-231257 0870 3 F Clarifications on obtaining analytics information from MDAF 18.4.0 2023-12 SP#102 SP-231257 0881 3 F Modification to Federated Learning feature description and call flow 18.4.0 2023-12 SP#102 SP-231257 0883 4 F Updates for ML Model training related procedures and services 18.4.0 2023-12 SP#102 SP-231257 0901 2 F Movement behaviour analytics updates 18.4.0 2023-12 SP#102 SP-231257 0904 2 F Correction on status report of FL Training 18.4.0 2023-12 SP#102 SP-231257 0906 4 F Clarification on Federated Learning between NWDAFs 18.4.0 2023-12 SP#102 SP-231257 0911 3 F Replace the below the cell level with longitude and latitude level 18.4.0 2023-12 SP#102 SP-231275 0914 3 F Data collection from UPF 18.4.0 2023-12 SP#102 SP-231257 0916 2 F Clarification on the ML Model Metric in Federated Learning 18.4.0 2023-12 SP#102 SP-231257 0922 3 F Clarification on movement behaviour analytics 18.4.0 2023-12 SP#102 SP-231257 0923 2 F Clarification on procedure for ML Model Training 18.4.0 2023-12 SP#102 SP-231275 0924 2 F Corrections to UPF data collection in NWDAF 18.4.0 2023-12 SP#102 SP-231257 0925 2 F Alignment of parameters for Federated Learning operation 18.4.0 2023-12 SP#102 SP-231257 0933 4 F Correcting clause 6.2B.7 18.4.0 2023-12 SP#102 SP-231242 0935 - A Wrong NF in 6.2.2.1, bullet 3 18.4.0 2023-12 SP#102 SP-231257 0939 3 F Alignments for ML Model provisioning content and related services 18.4.0 2023-12 SP#102 SP-231257 0943 3 F Corrections of ML Model Training Service 18.4.0 2023-12 SP#102 SP-231257 0946 1 F Clarification on registration and discovery procedure for FL 18.4.0 2023-12 SP#102 SP-231257 0947 1 F Clarification on the ML Model metric for FL 18.4.0 2023-12 SP#102 SP-231257 0949 2 F Update data collected by NWDAF for location Accuracy Analytics 18.4.0 2023-12 SP#102 SP-231257 0950 2 F Add the velocity estimation to the input data for relative proximity analytics 18.4.0 2023-12 SP#102 SP-231257 0953 1 F Remove EN related to parameters of Nnwdaf_RoamingData_Subscribe service operation 18.4.0 2023-12 SP#102 SP-231257 0962 3 F Correction on usage of untrusted AF data source rating 18.4.0 2023-12 SP#102 SP-231253 0970 3 F Updates to AI/ML functionality descriptions related to E2E data volume transfer time analytics 18.4.0 2023-12 SP#102 SP-231257 0972 2 F Clarification and correction on the Nnwdaf_MLModelMonitor_Notify service operation 18.4.0 2023-12 SP#102 SP-231257 0976 4 F Clarification on the analytics exposure in roaming case 18.4.0 2023-12 SP#102 SP-231258 0978 1 F Add Ndccf_DataManagement_Transfer service 18.4.0 2023-12 SP#102 SP-231258 0980 1 F Corrections for Analytics Accuracy Subscription Procedures of NWDAF 18.4.0 2023-12 SP#102 SP-231258 0985 1 F Update the contents of ML Model Provisioning 18.4.0 2023-12 SP#102 SP-231258 0987 1 F Update Location accuracy analytics. 18.4.0 2023-12 SP#102 SP-231258 0988 2 F Correction to Nadrf_MLModelManagement_StorageRequest service operation 18.4.0 2023-12 SP#102 SP-231258 0992 2 F Correction on ML Model accuracy information 18.4.0 2023-12 SP#102 SP-231258 0993 2 F Correction on MTLF-based ML Model Accuracy Monitoring 18.4.0 2023-12 SP#102 SP-231258 0994 2 F Align and unify description on AnLF Analytics Accuracy Monitoring 18.4.0 2023-12 SP#102 SP-231258 1003 1 F Clarifications to Analytics/ML Model Accuracy Monitoring Functionality 18.4.0 2023-12 SP#102 SP-231258 1004 1 F Clarifications to Contents of Analytics exposure 18.4.0 2023-12 SP#102 SP-231258 1016 2 F Alignments for Analytics Exposure and related services 18.4.0 2023-12 SP#102 SP-231258 1017 - F Correction on procedure for ML Model Storage in ADRF 18.4.0 2023-12 SP#102 SP-231253 1019 4 F Resolve EN for end-to-end data volume transfer time analytics 18.4.0 2023-12 SP#102 SP-231258 1020 3 F Corrections on parameters for PFD Determination 18.4.0 2024-03 SP#103 SP-240094 0856 3 F Removing Editor's Note of the Output of the Network Performance Analytics 18.5.0 2024-03 SP#103 SP-240099 0903 4 F Update the consumer of ML Model Provisioning services 18.5.0 2024-03 SP#103 SP-240099 0926 2 D Editorial changes to RE-NWDAF 18.5.0 2024-03 SP#103 SP-240099 0938 4 F Use of ML Model Interoperability Indicator and Vendor ID in Discovery 18.5.0 2024-03 SP#103 SP-240099 0945 4 F Clarification on analytics collection from MDAF 18.5.0 2024-03 SP#103 SP-240099 0951 7 F Source of the PFD contained in PFD information retrieved from UDR 18.5.0 2024-03 SP#103 SP-240099 0967 2 F Editorial clean-up for the description of Figures and Procedures 18.5.0 2024-03 SP#103 SP-240099 0981 4 F Solve NAT issue in UE data collection 18.5.0 2024-03 SP#103 SP-240099 0986 5 F Clarification on meaning of accuracy 18.5.0 2024-03 SP#103 SP-240099 0996 6 F Harmonising terminology related to Accuracy 18.5.0 2024-03 SP#103 SP-240099 1005 2 F Clarifications to Analytics Exposure and data collection in Roaming Case 18.5.0 2024-03 SP#103 SP-240083 1013 1 A Addressing EN on reference of MDA service 18.5.0 2024-03 SP#103 SP-240099 1015 1 F Clarification for ADRF discovery 18.5.0 2024-03 SP#103 SP-240094 1022 - F DNAI parameter removal from E2E data volume transfer time predictions 18.5.0 2024-03 SP#103 SP-240083 1024 1 A Correction on user consent for retrieving data stored in the ADRF/NWDAF 18.5.0 2024-03 SP#103 SP-240099 1025 1 F Correction on ML Model retrieval 18.5.0 2024-03 SP#103 SP-240094 1027 1 F Clarification on E2E data volume transfer time analytics 18.5.0 2024-03 SP#103 SP-240099 1029 1 F Clarification on Federated Learning between NWDAFs 18.5.0 2024-03 SP#103 SP-240099 1030 1 F Clarification on ML Model Metric in Federated Learning 18.5.0 2024-03 SP#103 SP-240099 1031 1 F Corrections to ML Model Training 18.5.0 2024-03 SP#103 SP-240099 1032 1 F Corrections to Analytics ID and Service operation 18.5.0 2024-03 SP#103 SP-240099 1039 1 F Clarification on output strategy in output information of analytic 18.5.0 2024-03 SP#103 SP-240099 1040 1 F Wrong reference number of other specification 18.5.0 2024-03 SP#103 SP-240099 1041 1 F Miscellaneous corrections for TS 23.288 18.5.0 2024-03 SP#103 SP-240191 1043 1 F Clarifications on ground truth retrieval of Location Accuracy Analytics 18.5.0 2024-03 SP#103 SP-240191 1045 2 F Adding Analytics Information in the ML Model Monitoring service 18.5.0 2024-03 SP#103 SP-240191 1048 1 F Qos related correction 18.5.0 2024-03 SP#103 SP-240191 1049 - F Clarification on the ML Model Metric in Federated Learning 18.5.0 2024-03 SP#103 SP-240191 1050 1 F Miscellaneous corrections 18.5.0 2024-03 SP#103 SP-240115 1052 1 F Alignment of unclear description of 3DA Data Management Service 18.5.0 2024-03 SP#103 SP-240191 1053 1 F Alignment of table 5A.2-1 and table 6.2.2.1-2 18.5.0 2024-03 SP#103 SP-240191 1054 3 F Clarification of analytics accuracy information 18.5.0 2024-03 SP#103 SP-240191 1056 1 F Clarification of training data in federated learning process 18.5.0 2024-03 SP#103 SP-240191 1059 2 F Corrections related to ML model identifier 18.5.0 2024-03 SP#103 SP-240115 1061 2 F Clarification related to the information exposed by the 5GC to NSCE server 18.5.0 2024-03 SP#103 SP-240083 1063 1 A Correction on Data Management 18.5.0 2024-03 SP#103 SP-240115 1064 2 F Correction on NWDAF discovery and selection 18.5.0 2024-03 SP#103 SP-240191 1066 - F FL related corrections 18.5.0 2024-03 SP#103 SP-240191 1067 1 F Correction to the FL capability type 18.5.0 2024-03 SP#103 SP-240191 1071 - F Alignments for the Accuracy checking capability in TS 23.288 18.5.0 2024-03 SP#103 SP-240191 1072 2 F Modification about the Analytics Accuracy of the ML Model 18.5.0 2024-03 SP#103 SP-240094 1074 2 F Add KPI and references. Removal of Input Data general Note for the end-to-end data volume transfer time analytics 18.5.0 2024-06 SP#104 SP-240584 1076 - A Wrong service operation used in prepared analytics subscription transfer 18.6.0 2024-06 SP#104 SP-240584 1080 2 A Correction on ML Model Provisioning with Multiple Analytics IDs and Filters 18.6.0 2024-06 SP#104 SP-240592 1084 3 F Corrections to procedures of e2e data volume transfer time analytics 18.6.0 2024-06 SP#104 SP-240595 1087 1 F Clarification on QoS sustainability analytics 18.6.0 2024-06 SP#104 SP-240595 1091 2 F Update for ML Model sharing in FL 18.6.0 2024-09 SP#105 SP-241243 1105 - F Clarification on the consumer of ML model provisioning service operation 18.7.0 2024-09 SP#105 SP-241243 1123 3 F Alignment on ML Model update description 18.7.0 2024-09 SP#105 SP-241243 1140 1 D Updating Abbreviations in TS 23.288 18.7.0 2024-09 SP#105 SP-241243 1143 2 F Correction NWDAF discovery and selection. 18.7.0 2024-09 SP#105 SP-241264 1126 3 B General inference procedure for vertical federated learning 19.0.0 2024-09 SP#105 SP-241264 1164 3 B Support for LMF to retrieve ML Model of AI/ML based positioning 19.0.0 2024-09 SP#105 SP-241416 1165 5 B Public UE IP address exposure 19.0.0 2024-09 SP#105 SP-241264 1171 3 B Registration and Discovery procedure for Vertical Federated Learning among NWDAF(s) and/or AF(s) with NWDAF as the VFL server 19.0.0 2024-09 SP#105 SP-241268 1180 2 B Support of QoS Substainability Analytics for UAS 19.0.0 2024-09 SP#105 SP-241264 1185 3 B High level feature description for VFL 19.0.0 2024-12 SP#106 SP-241486 1104 14 B New analytics ID to support Signalling storm Mitigation and Prevention 19.1.0 2024-12 SP#106 SP-241486 1132 11 B Support of QoS and policy assistance analytics 19.1.0 2024-12 SP#106 SP-241486 1198 14 B Refinements for VFL feature 19.1.0 2024-12 SP#106 SP-241486 1246 8 B KI#2 - Update of VFL training and inference 19.1.0 2024-12 SP#106 SP-241486 1208 12 B Update the general inference procedure for vertical federated learning to resolve ENs 19.1.0 2024-12 SP#106 SP-241486 1134 21 B General training procedure for Vertical Federated Learning between NWDAF(s) and AF(s) 19.1.0 2024-12 SP#106 SP-241486 1161 9 B High-level description for Vertical Federated Learning when AF is as Server. 19.1.0 2024-12 SP#106 SP-241486 1196 6 B Addressing the EN about model provision for AI positioning 19.1.0 2024-12 SP#106 SP-241486 1201 3 B NWDAF collects data from LCS to train ML model for AI positioning 19.1.0 2024-12 SP#106 SP-241471 1203 1 A Clarification on the service consumers of Nnwdaf, Ndccf, Nmfaf related services 19.1.0 2024-12 SP#106 SP-241471 1211 1 A Correction on ML model Notify service 19.1.0 2024-12 SP#106 SP-241471 1216 1 A Add missing MFAF Services and Service operations 19.1.0 2024-12 SP#106 SP-241471 1227 2 A Clarification on update ML model in ADRF 19.1.0 2024-12 SP#106 SP-241471 1229 2 A Removal of 3GPP WG references in final TS 19.1.0 2024-12 SP#106 SP-241495 1238 6 F Correction on public IP address reporting 19.1.0 2024-12 SP#106 SP-241493 1240 3 F Adding a list of UEs as input for NWDAF analytics 19.1.0 2024-12 SP#106 SP-241493 1241 1 F Updates to Relative Proximity Analytics 19.1.0 2024-12 SP#106 SP-241484 1243 2 F Corrections to QoE measurements 19.1.0 2024-12 SP#106 SP-241471 1245 1 A Incorrect reference in NF load analytic 19.1.0 2024-12 SP#106 SP-241486 1253 6 B Support AI/ML model performance monitoring by NWDAF 19.1.0 2024-12 SP#106 SP-241471 1254 - A Corrections to roaming procedures 19.1.0 2024-12 SP#106 SP-241471 1264 A Correction on data collection and storage description 19.1.0 2024-12 SP#106 SP-241486 1269 2 B High level description refinement of NWDAF initiated VFL training 19.1.0 2024-12 SP#106 SP-241484 1270 3 F Corrections on Analytics metadata information 19.1.0 2024-12 SP#106 SP-241486 1271 1 B KI#1: Using New LMF DataCollection service to collect input data for model training 19.1.0 2024-12 SP#106 SP-241486 1275 1 B Update to model provisioning for LMF-based AIML positioning 19.1.0 2025-03 SP#107 SP-250041 1236 12 B KI#2: VFL services 19.2.0 2025-03 SP#107 SP-250041 1255 3 F Support of QoS policy assistance information analytics 19.2.0 2025-03 SP#107 SP-250041 1302 3 B Modifications on ML Model retrieval service 19.2.0 2025-03 SP#107 SP-250044 1308 - A Correction on ML Model monitoring service operation 19.2.0 2025-03 SP#107 SP-250044 1310 - A Implement agreed ML Model update parameter 19.2.0 2025-03 SP#107 SP-250037 1311 1 F Correction on MFAF related service 19.2.0 2025-03 SP#107 SP-250041 1313 1 F Clarifying Signalling Storm Analytics 19.2.0 2025-03 SP#107 SP-250041 1322 - F Adding missing parts for VFL 19.2.0 2025-03 SP#107 SP-250041 1326 8 F Editorial improvement on QoS and policy assistance analytics 19.2.0 2025-03 SP#107 SP-250041 1327 4 B Support of VFL model training and inference with client intermediate results sharing between VFL clients 19.2.0 2025-03 SP#107 SP-250041 1329 4 F EN removal for clarification of VFL high level description 19.2.0 2025-03 SP#107 SP-250041 1330 1 B Clarifications on VFL general procedure 19.2.0 2025-03 SP#107 SP-250041 1331 1 B The related definitions for VFL and HFL 19.2.0 2025-03 SP#107 SP-250042 1333 9 B Resolve some ENs in the vertical federated learning inference procedure 19.2.0 2025-03 SP#107 SP-250042 1338 13 C Resolving ENs for VFL 19.2.0 2025-03 SP#107 SP-250042 1342 2 C Sample update during VFL training 19.2.0 2025-03 SP#107 SP-250037 1344 4 C Addition of delay threshold match indication 19.2.0 2025-03 SP#107 SP-250042 1353 1 B Updates on VFL training and VFL inference to remove ENs 19.2.0 2025-03 SP#107 SP-250042 1354 1 F Clarification and alignment on signalling storm analytics 19.2.0 2025-03 SP#107 SP-250042 1355 4 B Enhancements for the accuracy monitoring of VFL training 19.2.0 2025-03 SP#107 SP-250042 1363 1 B KI2: Addressing ENs for VFL 19.2.0 2025-03 SP#107 SP-250042 1364 3 C KI#1 - Further clarification on ML Model performance monitoring for AI/ML positioning 19.2.0 2025-03 SP#107 SP-250042 1367 4 B KI#2 - update to VFL inference procedure 19.2.0 2025-03 SP#107 SP-250062 1368 1 F Editorial Clarifications for AF retreival of UE public IP address 19.2.0 2025-03 SP#107 SP-250042 1370 1 F KI#2 - update to registration and discovery procedure 19.2.0 2025-03 SP#107 SP-250042 1371 6 B KI#2 - update to VFL preparation procedure 19.2.0 2025-03 SP#107 SP-250044 1374 2 A Supplement of functional description of NWDAF 19.2.0 2025-03 SP#107 SP-250044 1376 1 A ML Model storage description alignment 19.2.0 2025-03 SP#107 SP-250042 1377 1 B Clarifications on intermediate training result and intermediate model training information 19.2.0 2025-03 SP#107 SP-250041 1384 - C KI2: Addressing EN in VFL training 19.2.0 2025-03 SP#107 SP-250042 1388 2 F Clarification on LMF as service consumer for ML Model Training 19.2.0 2025-03 SP#107 SP-250037 1389 1 F Correlate the Slice Load to an AOI when location is provided 19.2.0 2025-03 SP#107 SP-250042 1391 1 F KI#4: Minor Clarifications and Corrections 19.2.0 2025-03 SP#107 SP-250044 1396 1 A Correction on accuracy monitoring description and procedure 19.2.0 2025-03 SP#107 SP-250037 1399 2 F User consent check when correlating UE data collection and NWDAF data request 19.2.0
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1 Scope
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The present document specifies the use of the 5G System (5GS) considering common functional architecture, procedures and information flows needed to support mission critical services encompassing the common services core architecture.
The corresponding service requirements applied in 3GPP TS 22.179 [11], 3GPP TS 22.280 [12], 3GPP TS 22.281 [13], 3GPP TS 22.282 [14] and 3GPP TS 22.289 [22] also apply here.
The corresponding MC service specific procedures and information flows are defined in 3GPP TS 23.280 [3], 3GPP TS 23.379 [6], 3GPP TS 23.281[4], 3GPP TS 23.282 [5] and 3GPP TS 23.283 [23].
The present document is applicable primarily to mission critical services using 3GPP access (5G NR and/or E-UTRA) and non-3GPP access (WLAN, Satellite and/or wireline) based on the 5GC architecture defined in 3GPP TS 23.501 [7], 3GPP TS 23.247 [15] and 3GPP TS 23.304 [17].
The common functional architecture to support mission critical services can be used for public safety applications and for general commercial applications e.g. utility companies and railways.
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2 References
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The following documents contain provisions which, through reference in this text, constitute provisions of the present document.
- References are either specific (identified by date of publication, edition number, version number, etc.) or non‑specific.
- For a specific reference, subsequent revisions do not apply.
- For a non-specific reference, the latest version applies. In the case of a reference to a 3GPP document (including a GSM document), a non-specific reference implicitly refers to the latest version of that document in the same Release as the present document.
[1] 3GPP TR 21.905: "Vocabulary for 3GPP Specifications".
[2] 3GPP TS 23.228: "IP Multimedia Subsystem (IMS); Stage 2".
[3] 3GPP TS 23.280: "Common functional architecture to support mission critical services; Stage 2".
[4] 3GPP TS 23.281: "Functional architecture and information flows to support Mission Critical Video (MCVideo); Stage 2".
[5] 3GPP TS 23.282: "Functional architecture and information flows to support Mission Critical Data (MCData); Stage 2".
[6] 3GPP TS 23.379: "Functional architecture and information flows to support Mission Critical Push To Talk (MCPTT); Stage 2".
[7] 3GPP TS 23.501: "System architecture for the 5G System (5GS)".
[8] 3GPP TS 23.002: "Network Architecture".
[9] 3GPP TS 23.503: "Policy and Charging Control Framework for the 5G System (5GS); Stage 2".
[10] 3GPP TS 23.502: "Procedures for the 5G System (5GS)".
[11] 3GPP TS 22.179: "Mission Critical Push to Talk (MCPTT); Stage 1".
[12] 3GPP TS 22.280: "Mission Critical Services Common Requirements (MCCoRe); Stage 1".
[13] 3GPP TS 22.281: "Mission Critical (MC) Video".
[14] 3GPP TS 22.282: "Mission Critical (MC) Data".
[15] 3GPP TS 23.247: "Architectural enhancements for 5G multicast-broadcast services; Stage 2".
[16] 3GPP TS 23.468: "Group Communication System Enablers for LTE (GCSE_LTE); Stage 2".
[17] 3GPP TS 23.304: "Proximity based Service (ProSe) in the 5G System (5GS); Stage 2".
[18] 3GPP TS 23.237: "IP Multimedia Subsystem (IMS) Service Continuity; Stage 2".
[19] 3GPP TS 38.331: "NR; Radio Resource Control (RRC) protocol specification".
[20] 3GPP TS 23.479: "UE MBMS APIs for Mission Critical Services".
[21] 3GPP TS 26.502: "5G Multicast-Broadcast User Service Architecture".
[22] 3GPP TS 22.289: "Mobile communication system for railways".
[23] 3GPP TS 23.283: "Mission Critical Communication Interworking with Land Mobile Radio Systems".
[24] IETF RFC 9330:"Low Latency, Low Loss, Scalable Throughput (L4S) Internet Service: Architecture".
[25] Void
[26] 3GPP TS 23.273: "5G System (5GS) Location Services (LCS); Stage 2".
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3 Definitions of terms, symbols and abbreviations
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3.1 Terms
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For the purposes of the present document, the terms given in 3GPP TR 21.905 [1] and the following apply. A term defined in the present document takes precedence over the definition of the same term, if any, in 3GPP TR 21.905 [1].
For the purposes of the present document, the following terms given in 3GPP TS 23.280 [3] apply:
MC service
MC service user
MC service UE
MC system
MC user
MC gateway UE
MC client
For the purposes of the present document, the following terms given in 3GPP TS 23.247 [15] apply:
MBS session
Broadcast MBS session
Multicast communication service
Multicast MBS session
Broadcast communication service
MBS service area
MB-SMF service area
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3.2 Symbols
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Void.
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3.3 Abbreviations
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For the purposes of the present document, the abbreviations given in 3GPP TR 21.905 [1] and the following apply. An abbreviation defined in the present document takes precedence over the definition of the same abbreviation, if any, in 3GPP TR 21.905 [1].
ECN Explicit Congestion Notification
L4S Low Latency, Low Loss and Scalable Throughput
NPN Non-Public Network
NTN Non-Terrestrial Network
PNI-NPN Public Network Integrated Non-Public Network
SNPN Stand-alone Non-Public Network
NID Network Identifier
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4 MC system resource requirements
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4.1 Multiple Access
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4.1.1 General
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5GS provides simultaneous integration of different access types 3GPP and non-3GPP (wireline and wireless), defined in 3GPP TS 23.501 [7]. Accordingly, this enables the MC service UE to be used under both stationary and non-stationary conditions.
With the convergence of multiple access technologies in 5GS, service features can be assigned agnostically without taking the access type into account for the MC service user.
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4.1.2 Requirements
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With the use of 5GS, MC services shall be available via 3GPP access as well as via non-3GPP access. To enable access to the MC system, the use of the various access types shall be authorized by the 5GC. The simultaneous use of different access types (Access Traffic Steering, Switching and Splitting) is defined in 3GPP TS 23.501 [7] and its characteristics are subject to respective operators policy.
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4.2 Session connectivity
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4.2.1 General
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The access from 5GS to the MC service environment takes place via the Data Network (DN) in accordance with 3GPP TS 23.501 [7]. A Data Network Name (DNN) as part of the 5GS user profile allows access to the Data Network with up to 8 connectivity sessions (PDU sessions) each with up to 64 communication flows (QoS flows). Different data networks require different DNNs.
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4.2.2 Requirements
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For MC service UEs who only utilize 5GS, a single DNN may be used for:
- for the SIP-1 reference point;
- for the HTTP-1 reference point; and
- for the CSC-1 reference point.
The DNN shall be made available to the MC service UE either via UE (pre)configuration or via initial UE configuration on a per HPLMN and optionally also per VPLMN basis.
NOTE 1: The Data Network access can also be shared with the "IMS" access taking into account the communication flow limits.
The MC service UE may exploit secondary authentication/authorization by a DN-AAA server during the establishment of session connectivity as specified in 3GPP TS 23.501 [7] using the Extensible Authentication Protocol (EAP) to access the DN identified by the MC service DNN. If required, DN access credentials shall be made available to the MC service UE via initial MC service UE configuration on a per DNN basis.
The DN connection to the DNN defined within the present subclause can be of PDU session type "IPv4", "IPv6", "IPv4v6", Ethernet or Unstructured (see 3GPP TS 23.501 [7]). If a DN connection to an DNN defined within the present subclause is of type "IPv4v6" then the MC service client shall use configuration data to determine whether to use IPv4 or IPv6.
NOTE 2: In accordance to 3GPP TS 23.501 [7], the use of PDU session type Ethernet and Unstructured has limited support in the Session and Service Continuity context.
For MC service UEs who utilize EPS and 5GS 3GPP TS 23.280 [3] clause 5.2.7 applies.
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4.3 QoS characteristics
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4.3.1 General
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In 5GS, quality of service is enforced at QoS flow level and corresponding packets are classified and marked with an identifier in accordance with 3GPP TS 23.501 [7]. Every QoS flow is characterized by a QoS profile provided by the 5GC, and can be used for all connectivity types (PDU sessions) in accordance with 3GPP TS 23.501 [7].
5G QoS characteristics, standardized or non-standardized, are indicated through the 5QI value in accordance with 3GPP TS 23.501 [7]. Standardized 5QI values have a one-to-one mapping to a standardized combination of 5G QoS characteristics and non-standardized 5QI values allows a dynamic assignment of QoS parameter values.
NOTE 1: The use of non-standardized 5QI values can be subject for harmonisation within the individual user area.
The QoS parameter Allocation Retentions Priority (ARP) determines the priority level, the pre-emption capability and the pre-emption vulnerability of each QoS flow. ARP priority level defines the relative importance of a resource request to allow in deciding whether a new QoS Flow may be accepted or needs to be rejected in the case of resource limitations in accordance with 3GPP TS 23.501 [7].
NOTE 2: The use of ARP is regulated by the individual MC service.
The use of Multicast Broadcast Services (MBS) for MC services shall apply QoS handling as determined by 3GPP TS 23.247 [15].
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4.3.2 QoS requirements for general purposes
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The selection, deployment, initiation, and termination of QoS signalling and resource allocation shall consider the QoS mechanisms described in 3GPP TS 23.501 [7], 3GPP TS 23.502 [10], 3GPP TS 23.503 [9] and 3GPP TS 23.247 [15] for MBS.
MC system as well as MC service UE may share one DNN using multiple QoS flows for the settlement of MC services, application plane and signalling plane.
For the transport of SIP-1 reference point signalling, the standardized 5QI value of 69 in accordance with 3GPP TS 23.501 [7] shall be used.
For the transport of HTTP-1 reference point signalling, the standardized 5QI value of 8 in accordance with 3GPP TS 23.501 [7] or better shall be used.
MC services shall use standardized 5QI values or may use non-standardized 5QI values in accordance with 3GPP TS 23.501 [7].
When the MC system utilizes IMS services, at least one QoS flow shall be associated for IMS signalling. The generic mechanisms for interaction between QoS and session signalling applicable for the use of IMS in the 5GS context are defined in 3GPP TS 23.228 [2].
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4.3.3 QoS requirements for Mission Critical Push to Talk
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4.3.3.1 General
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The requirements listed here apply for the use of 5GS and replace the corresponding requirements in 3GPP TS 23.379 [6].
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4.3.3.2 5QI values for MCPTT
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The MCPTT system may use the N5 reference point or Rx reference point for direct interaction with 5GS PCF to determine the required QoS flow parameters. Alternatively, the MCPTT system may use the N33 reference point for indirect interaction with 5GS NEF.
For the use of MBS, the MCPTT system may interact with the PCF/MB-SMF/NEF/MBSF to provide the corresponding QoS information.
A QoS flow (unicast or multicast/broadcast) for an MCPTT voice call and MCPTT-4/MCPTT-9 reference point signalling shall utilize 5QI value 65 in accordance with 3GPP TS 23.501 [7] and 3GPP TS 23.247 [15].
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4.3.3.3 Use of priorities
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The QoS flow (unicast or multicast/broadcast) for an MCPTT emergency call shall have highest priority level among MCPTT call types. The QoS flow (unicast or multicast/broadcast) for MCPTT imminent peril call shall have higher priority level than one for a MCPTT call.
Depending on operators' policy, the MCPTT system may be able to request modification of the priority (ARP) of an established QoS flow (unicast or multicast/broadcast).
NOTE: Operators' policy takes into account regional/national requirements.
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4.3.4 QoS requirements for Mission Critical Video
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4.3.4.1 General
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The requirements listed here apply for the use of 5GS and replace the corresponding requirements in 3GPP TS 23.281 [4].
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4.3.4.2 5QI values for MCVideo
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The MCVideo system may use the N5 reference point or Rx reference point for direct interaction with 5GS PCF to determine the required QoS flow parameters. Alternatively, the MCVideo system may use the N33 reference point for indirect interaction with 5GS NEF.
For the use of MBS, the MCVideo system may interact with the PCF/MB-SMF/NEF/MBSF to provide the corresponding QoS information.
Video media and control of the video media may use independent QoS flows (unicast or multicast/broadcast) and utilizes 5QI values depending on the MCVideo mode of the MCVideo call/session, as per table 4.3.4.2-1.
Table 4.3.4.2-1: MCVideo mode associated 5QI values
MCVideo mode
5QI value utilized
(in accordance with 3GPP TS 23.501 [7])
Urgent real-time mode
67
Non-urgent real-time mode
67
Non real-time mode
4
For transmission and reception control signalling, the 5QI value 69 is recommended in accordance with 3GPP TS 23.501 [7] and 3GPP TS 23.247 [15].
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4.3.4.3 Use of priorities
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The MCVideo audio media and video media may transmit over dedicated QoS flows (unicast or multicast/broadcast), in which case the priority for each QoS flow (unicast or multicast/broadcast) is determined by the operator policy.
MCVideo services shall be able to use ARP pre-emption capability and the pre-emption vulnerability of each individual QoS flow (unicast or multicast/broadcast) according to operators' policy. Depending on operators' policy, the MCVideo system may be able to request modification of the priority (ARP) of an established QoS flow (unicast or multicast/broadcast).
NOTE: Operator policy takes into account regional/national requirements.
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4.3.5 QoS requirements for Mission Critical Data
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4.3.5.1 General
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The requirements listed here apply for the use of 5GS and replace the corresponding requirements in 3GPP TS 23.282 [5].
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4.3.5.2 5QI values for MCData
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The MCData system may use the N5 reference point or Rx reference point for direct interaction with 5GS PCF to determine the required QoS flow parameters. Alternatively, the MCData system may use the N33 reference point for indirect interaction with 5GS NEF.
For the use of MBS, the MCData system may interact with the PCF/MB-SMF/NEF/MBSF to provide the corresponding QoS information.
A QoS flow (unicast or multicast/broadcast) for MCData media may utilize standardized 5QI value 70 or may utilize non-standardized 5QI values in accordance with 3GPP TS 23.501 [7] and 3GPP TS 23.247 [15].
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4.3.5.3 Use of priorities
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The QoS flows (unicast or multicast/broadcast) for MCData emergency communications shall have highest priority level among MCData communication types. The QoS flow (unicast or multicast/broadcast) for MCData imminent peril call shall have higher priority level than one for a MCData communication.
MCData services shall be able to use ARP pre-emption capability and the pre-emption vulnerability of each individual QoS flow (unicast or multicast/broadcast) according to operators' policy.
NOTE: Operators' policy takes into account regional/national requirements.
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4.4 Network Slicing
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4.4.1 General
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Network slicing in accordance with 3GPP TS 23.501 [7] can be used for several purposes such as to separate MC service users, UEs as well as applications in accordance with the various QoS requirements independent from 3GPP or non-3GPP access.
The corresponding slice information identifies a network slice across the 5G core, access network and the UE. In accordance with 3GPP TS 23.501 [7] standardized and non-standardized slice selection information can be used.
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4.4.2 Requirements
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For the use of network slicing in the MC service context, the following minimum requirements in accordance with 3GPP TS 23.501 [7] shall be considered:
One network slice shall be assigned per PDU session and may benefit from a dedicated transmission resource allocation.
The network slicing for MC services follows the concepts defined in 3GPP TS 23.501 [7]. The Initial MC service UE configuration shall contain at least one network slice identity (S-NSSAI). Those S-NSSAIs shall be considered as part of the Default Configured S-NSSAI(s), and should be utilized by the MC service UE to form the Requested S-NSSAI(s) at registration as specified in 3GPP TS 23.501 [7].
If the MC service UE requests a slice which is subject to Network Slice-Specific Authentication and Authorization, the corresponding aspects as well as the MC service UE behaviour are to be followed as described in 3GPP TS 23.501 [7], and 3GPP TS 23.502 [10]. The corresponding credentials per S-NSSAI can be configured in the initial MC service UE configuration or UE (pre-)configuration.
The use of network slices corresponding to non-standardized NSSAIs across PLMN boundaries requires harmonisation in order to guarantee their availability.
Initial MC service UE configuration data may contain information for the PDU session to be used for each MC service (including among others the S-NSSAI).
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4.5 Use of public and non-public networks
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4.5.1 General
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MC services are service agnostic with respect to 5GS, i.e., the available service options are identical in both public networks (i.e. PLMN) and non-public networks (NPNs). A non-public network (NPN) can be deployed in organization defined premises and the 5G network services are provided to a defined set of users or organizations in accordance with 3GPP TS 23.501 [7].
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4.5.2 Requirements
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An MC system shall be able to utilize connectivity from public 5GS networks and non-public 5GS networks in accordance with 3GPP TS 23.501 [7].
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4.6 Migration
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4.6.1 General
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For the migration of an MC service user the general assumptions in 3GPP TS 23.280 [3] clause 5.2.9.1 are applied.
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4.6.2 Public network utilization
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Migrated MC service users should utilize the home PLMN of the partner MC system to access MC services in the partner MC system, however, utilizing the home PLMN of the primary MC system is not precluded.
NOTE 1: The above recommendation ensures the security policy of the partner MC system and is not compromised, the expected 5QIs are used on the 5GS to ensure that service‑level delay requirements are consistently met (which are especially at risk when the home PLMN of the primary MC system and the home PLMN of the partner MC system are far apart from a geographical point of view).
NOTE 2: Whether the home PLMN of partner MC systems or the home PLMN of the primary MC system is used to access MC services in partner MC systems is left to business agreements between MC service providers and is outside the scope of the present document.
NOTE 3: The MC service user's MCData message store will not be available when using the home PLMN of the partner MC system to access MC services in migration.
The MC service user profile enabled for migration shall be provisioned with configuration data that specifies which PLMNs supporting 5GS are to be selected when migrating to another MC system.
If the home PLMN of a partner MC system is different from the home PLMN of the primary MC system (i.e. migrating MC service users roam into the home PLMN of the partner MC system), then:
- 5GS‑level roaming is required between the home PLMN of the primary MC system and home PLMN of the partner MC system;
- the home PLMN of the partner MC system needs to enable local break-out for the DNNs in accordance to subclause 4.2.2 that identify the DNs of the partner MC system; and
- the 5GS user profile of the home PLMN of the primary MC system used by the MC service users who are allowed to migrate to the partner MC system needs to be provisioned with, and local break-out enabled for, the DNNs proposed in subclause 4.2.2 that identify the DNs of the partner MC system.
If the home PLMN of the partner MC system and the home PLMN of the primary MC system are the same (i.e. migrating MC service users continue to use the home PLMN of their primary MC system), then:
- the 5GS user profile of the home PLMN of the primary MC system utilized by the MC service users who are allowed to migrate to the partner MC system needs to be provisioned with the DNNs specified in subclause 4.2.2 that identify the DNs of the partner MC system.
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4.6.3 Non-Public network utilization
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When the NPN is a PNI-NPN as described in 3GPP TS 23.501 [7], the requirements in clause 4.6.2 are applicable.
When the NPN is a SNPN as described in 3GPP TS 23.501 [7], the requirements may be different in the following options.
Option 1: The SNPN utilized by the primary MC system and the SNPN utilized by the partner MC system are the same (i.e., migrating MC service users continue to use the SNPN of their primary MC system.)
- the 5GS user profile of the SNPN of the primary MC system utilized by the MC service users who are allowed to migrate to the partner MC system needs to be provisioned with the DNNs specified in subclause 4.2.2 that identify the DNs of the partner MC system.
Option 2: The partner MC system and the primary MC system utilize different SNPNs.
- the migrated MC service users shall utilize the SNPN of the partner MC system to access MC service in the partner MC system.
- the 5GS user profile of the SNPN of the partner MC system used by the MC service users who are allowed to migrate to the partner MC system needs to be provisioned with the DNNs proposed in subclause 4.2.2 that identify the DNs of the partner MC system.
- the MC service UE shall have credentials to access the SNPN of the partner MC system. UE may access using credentials owned by a Credentials Holder separate from the SNPN of the partner MC system.
Option 3: The partner MC system utilizes the PLMN and the primary MC system utilize SNPN.
- the migrated MC service users should utilize the PLMN of the partner MC system to access MC service in the partner MC system.
- 5GS‑level SNPN and PLMN interworking is required between the SNPN of the primary MC system and PLMN of the partner MC system if the migrated MC service users utilize the SNPN of the primary MC system to access MC service in the partner MC system.
- the 5GS user profile of the PLMN of the partner MC system used by the MC service users who are allowed to migrate to the partner MC system needs to be provisioned with the DNNs proposed in subclause 4.2.2 that identify the DNs of the partner MC system.
Option 4: The partner MC system utilizes the SNPN and the primary MC system utilize PLMN.
- the migrated MC service users should utilize the SNPN of the partner MC system to access MC service in the partner MC system.
- 5GS‑level SNPN and PLMN interworking is required between the PLMN of the primary MC system and SNPN of the partner MC system if the migrated MC service users utilize the PLMN of the primary MC system to access MC service in the partner MC system.
- the MC service UE shall have credentials to access the SNPN of the partner MC system. UE may access using credentials owned by a Credentials Holder separate from the SNPN of the partner MC system.
- the 5GS user profile of the SNPN of the partner MC system used by the MC service users who are allowed to migrate to the partner MC system needs to be provisioned with the DNNs proposed in subclause 4.2.2 that identify the DNs of the partner MC system.
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4.7 Architectural aspects of MC services using MBS
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4.7.1 General
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The main purpose of 5G Multicast-Broadcast Service (MBS) use by mission critical services is to provide efficient downlink delivery of user traffic in group calls and communications. The architectural figures in this clause are aligned with the 5GS architecture for MBS shown in Figure 5.1-2 of 3GPP TS 23.247 [15], which identifies both mandatory and optional functional entities and interfaces, in reference point representation, available for use by the MC services.
Multicast and broadcast communication services in 5G for MC group communications rely on the creation and establishment of MBS sessions to deliver user data in downlink. Shared and individual delivery from the MC service server to multiple MC users (i.e., users affiliated to a certain MC group) is supported either as point-to-point or point-to-multipoint over the radio. The MBS sessions are either broadcast or multicast type and consist of one or multiple QoS flows for different service requirements. For the broadcast MBS session or local MBS session, the MBS service area is configured with the MBS session.
NOTE 1: Support of MBS and specific session types is an implementation choice.
NOTE 2: Aspects related to MC services over local MBS sessions and location dependent broadcast services are considered according to 3GPP TS 23.247 [15] clause 6.2 and clause 7.3.4, respectively.
Within this arrangement, the MC service server decides whether to create broadcast or multicast MBS sessions to be associated with certain MC groups. The 5GC adaptively decides whether to deliver the MBS traffic from the MB-UPF in the form of shared delivery or individual delivery, where the latter is applicable to multicast MBS sessions only. The NG-RAN decides to utilize point-to-point or point-to-multipoint delivery methods applicable for shared delivery only. MBS provides reliability enhancements and minimizes loss of information, e.g., due to mobility and handover.
MBS group scheduling mechanism enables simultaneous reception of MBS and unicast user traffic by the MC service UEs. The UEs can receive broadcast MBS sessions irrespective of their RRC state (i.e., connected, inactive or idle) and multicast sessions only in RRC‑CONNECTED and RRC-INACTIVE state.
The following capabilities (non-exhaustive list) provided by MBS could be used by MC service servers as described in 3GPP TS 23.247 [15]:
- MBS session creation;
- MBS session update;
- MBS session release;
- MBS session ID allocation;
- Transparent MBS Data forwarding;
- Dynamic PCC control for MBS session;
- UE's MBS assistance information provision.
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4.7.2 General on-network architecture for use of MBS by MC services
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Figure 4.7.2-1 presents a high-level architectural view of mission critical services when using MBS. The shown architecture is consistent with 3GPP TS 23.501 [7] and 3GPP TS 23.247 [15].
MC services use MBS control plane capabilities by initiating access via Nmb13, Nmb10 or N33. MBS user plane capabilities can be accessed via N6mb or Nmb8. MC service servers can initiate access to MBS PCC capabilities supported by PCF via N5 or N33. If the MC service server and the 5GS are in different trust domains with respect to MBS, N33 needs to be used to gain access to the MBS control plane capabilities and the PCC capabilities.
The 5G-GC1 reference point, which exists between the MC service client and the MC service server, is used for application layer signalling for the control of mission critical service delivery over MBS session. The functions of this reference point are defined in clause 7.3.
Figure 4.7.2-1: Architectural view of a mission critical system when using MBS
NOTE 1: Support of interfaces associated to 5GS optional entities (e.g. MBSF, MBSTF, NEF) is necessary only if features enabled by these entities are supported.
NOTE 2: When the MC service server uses MBS, the N5 reference point is used as described in the present document.
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4.7.3 Specific instantiations of on-network architecture for use of MBS by MC services
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4.7.3.1 Instantiation without optional entities and associated interfaces
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Figure 4.7.3.1-1 presents a high-level architectural view of mission critical services when using MBS without the presence or use of the optional entities (MBSF, MBSTF and NEF) and their associated interfaces. The shown architecture is a particularization of the general architecture shown in figure 4.7.3.1-1.
MC services use MBS control plane capabilities by initiating access via Nmb13. MBS user plane capabilities can be accessed via N6mb. MC service servers can initiate access to MBS PCC capabilities supported by PCF via N5.
Figure 4.7.3.1-1: Architectural view of a mission critical system when using MBS without optional MBS interfaces
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4.7.3.2 Instantiation without MBSF / MBSTF and associated interfaces
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Figure 4.7.3.2-1 presents a high-level architectural view of mission critical services when using MBS without the presence or use of the optional entities MBSF and MBSTF and their associated interfaces. The shown architecture is a particularization of the general architecture shown in figure 4.7.2-1.
MC services use MBS control plane capabilities by initiating access via Nmb13 or N33. MBS user plane capabilities can be accessed via N6mb. MC service servers can initiate access to MBS PCC capabilities supported by PCF via N5 or N33. If the MC service server and the 5GS are in different trust domains with respect to MBS, N33 needs to be used to gain access to the MBS control plane capabilities and the PCC capabilities.
Figure 4.7.3.2-1: Architectural view of a mission critical system when using MBS without optional MBSF/MBSTF entities and their associated interfaces
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4.7.3.3 Instantiation without NEF and associated interfaces
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Figure 4.7.3.3-1 presents a high-level architectural view of mission critical services when using MBS without the presence or use of the optional entity NEF and its associated interfaces. The shown architecture is a particularization of the general architecture shown in figure 4.7.2-1.
MC services use MBS control plane capabilities by initiating access via Nmb13 or Nmb10. MBS user plane capabilities can be accessed via N6mb or Nmb8. MC service servers can initiate access to MBS PCC capabililities supported by PCF via N5.
Figure 4.7.3.3-1: Architectural view of a mission critical system when using MBS without optional NEF entity and its associated interfaces
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4.7.4 Service layer‑based interworking between eMBMS and MBS
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Figure 4.7.4-1 presents a high-level architectural view of mission critical services interworking between eMBMS and MBS at the service layer. The shown architecture is consistent with 3GPP TS 23.247 [15], subclauses 5.2, 6.8 and configurations 2 and 3 in Annex A.
The interworking between eMBMS and MBS for mission critical operation is enabled by the Joint BM-SC, MBSF and MBSTF functional entity. MC services can use control plane capabilities by accessing the Joint entity directly via MB2-C or Nmb10 or indirectly (using NEF) via N33+Nmb5. User plane traffic delivery is supported via MB2-U or Nmb8. If the MC service server and the 5GS are in different trust domains with respect to MBS, N33 needs to be used to gain access to the MBS PCC capabilities.
Figure 4.7.4-1: Service layer‑based mission critical interworking between eMBMS and MBS
NOTE: Support of interfaces associated to 5GS optional entities (e.g., NEF) is necessary only if features enabled by these entities are supported.
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4.7.5 Application layer based interworking between eMBMS and MBS
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Figure 4.7.5-1 presents a high-level architectural view of mission critical services interworking between eMBMS and MBS at the application layer. The shown architecture does not use the MBSF/MBSTF entities defined in 3GPP TS 23.247 [15] and is inclusive of configuration 1 in Annex A of 3GPP TS 23.247 [15].
MC services initiate access to control plane capabilities via MB2-C (for eMBMS) and via Nmb13 or N33 (for MBS). User plane capabilities can be accessed via MB2-U (for eMBMS) and via N6mb (for MBS). MC service servers can initiate access to PCC capabilities via the Rx interface (for the PCRF in the EPS) and via the N5 or N33 interfaces (for the PCF in the 5GS). If the MC service server and the 5GS are in different trust domains with respect to MBS, N33 needs to be used to gain access to the MBS control plane capabilities and the PCC capabilities.
Figure 4.7.5-1: Application layer‑based mission critical interworking between eMBMS and MBS
NOTE: Support of interfaces associated to 5GS optional entities (e.g., NEF) is necessary only if features enabled by these entities are supported.
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4.7.6 General architecture showcasing use of MBS by UE for MC services
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Figure 4.7.6-1 presents a high-level system architecture that shows how the MC service UEs support the delivery of mission critical services through MBS. Figure 4.7.6-2 shows the functional model used by the UE, highlighting the conceptual MC MBS API used for information transfer within the UE. The shown system architecture and functional model are analogous to the models described in 3GPP TS 23.479 [20] and consistent with 3GPP TS 23.501 [7] and 3GPP TS 23.247 [15].
Figure 4.7.6-1: System architecture for MC MBS systems
NOTE: The shown architecture does not consider MBS User Services, i.e., signalling with MBSF/MBSTF, which is described in 3GPP TS 26.502 [21].
The conceptual MC MBS API resides between the MC service client and the conceptual MC MBS user agent.
Figure 4.7.6-2: Functional model highlighting the MC MBS API
The MC service client uses information received from the MC service server through MC signalling (e.g., announcements) and through application-level signalling (e.g., mappings of MBS sessions and MBS subchannels to specific MC service groups) to communicate with the conceptual MC MBS user agent via the conceptual MC MBS API, in order to establish and update the proper communication context between the entities. Multiple MC service clients can be supported by the MC MBS user agent. The conceptual MC MBS user agent presents data and information received from the UE's lower layers to each MC service client according to the most recently established communication context. The functionalities of the MC service client and of the MC MBS user agent are described in clauses 4.3.2 and 4.3.3 of 3GPP TS 23.479 [20]. The information flows and procedures described in 3GPP TS 23.479 [20] apply, with the following clarifications:
- References to "MBMS" (meaning 4G "eMBMS") are understood to be references to 5G "MBS";
- Unless used as in "multicast IP address", the stand-alone term "multicast" is understood as "broadcast or multicast";
- References to "SAI" are understood to be references to "MBS service areas", e.g., cell id, tracking area id, MBS frequency selection area id, as specified in 3GPP TS 23.274 [15];
- References to (e)MBMS 4G "bearer" are understood to be references to 5G "MBS session" and references to 4G "TMGI" are understood to be references to 5G "MBS session ID"; and
- "Cell information", used in cell information responses and cell update notifications in 5G, contains not only the id of the cell the MC UE is being served by, but also the RRC state of the MC service UE in the cell (i.e., active, inactive, idle). 5G cell updates notify not only changes of the serving cell, but also changes of RRC state for the MC UE, within the same cell.
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92c39d4e31dc10812fa1955d84ca0fc9
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23.289
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4.8 Use of 5G ProSe UE-to-network relay
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92c39d4e31dc10812fa1955d84ca0fc9
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23.289
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4.8.1 General
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The MC service shall support the capabilities for 5G ProSe UE-to-network relay. For this matter, 5G ProSe Layer-2 and 5G ProSe Layer-3 UE-to-network relaying techniques can be utilized, as described in 3GPP TS 23.304 [17]. The 5G ProSe Layer-3 UE-to-Network relaying technique may be done with or without the support of N3IWF, as described in 3GPP TS 23.304 [17].
A 5G ProSe UE-to-network relay supporting MC service UE provides means of connectivity and relaying of MC traffic to remote MC service UE(s). For this matter, the 5G ProSe UE-to-network Relay Discovery service allows the MC service remote UE to discover a potential UE-to-network relay UE supporting MC service in its proximity as described in 3GPP TS 23.304 [17]. Upon its discovery, the 5G ProSe Direct UE-to-network Relay Communication functionality is utilized to achieve communication to provide the MC service remote UE access to 5GS, and relay MC traffic via the UE-to-network relay UE over the NR PC5 reference point.
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92c39d4e31dc10812fa1955d84ca0fc9
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23.289
|
4.8.2 5G ProSe UE-to-network relay service requirements
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In order to enable 5G ProSe UE-to-network relaying capabilities – whether based on Layer-3 or Layer-2 UE-to-network relaying techniques, the MC system provides the appropriate parameters and configurations to the MC service UE(s).
As defined in 3GPP TS 23.304 [17], among these parameters are: Relay Service Code(s) (RSCs) which can be associated to a certain MC service group, User Info, ProSe Layer-2 Group ID and ProSe Group IP multicast address. Moreover, the MC service group ID is resolved to the ProSe Layer-2 Group ID and ProSe Group IP multicast address, which are utilized within the 5G ProSe Relay Discovery and 5G ProSe Direct Communication procedures, as described in 3GPP TS 23.304 [17]. Furthermore, the RSCs are utilized to restrict the necessary UE-to-network relay service and related procedures within members of a certain MC service group.
Moreover, in case of 5G ProSe Layer-3 UE-to-network relay with the support of N3IWF, the UE-to-network relay is provisioned with policies and parameters, among others suitable RSC(s), in order to support N3IWF access, as defined in 3GPP TS 23.304 [17].
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92c39d4e31dc10812fa1955d84ca0fc9
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23.289
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4.9 EPS interworking
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92c39d4e31dc10812fa1955d84ca0fc9
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23.289
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4.9.1 General
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Network deployments of MC services over 5GS may support interworking with EPS. EPS interworking aspects in 5G systems are specified in 3GPP TS 23.501 [7], 3GPP TS 23.502 [10], and 3GPP TS 23.503 [9].
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