hash stringlengths 32 32 | doc_id stringlengths 5 12 | section stringlengths 5 1.47k | content stringlengths 0 6.67M |
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30701f0da928d70591b1088aae4273d2 | 23.288 | 11.4.3 Naf_Inference_Unsubscribe service operation
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 11.4.4 Naf_Inference_Notify service operation
| Service operation name: Naf_Inference_Notify
Description: Notify VFL inference result.
Inputs, Required:
- Notification Correlation Information.
Inputs, Optional:
- Inference results:
- Set of the tuple (Analytics ID, Analytics specific parameters): this parameter shall be present if output analytics are reported.
- Validity period.
- Confidence.
- Analytics Metadata Information.
- Analytics Accuracy Information.
- Revised waiting time.
- Termination Request: this parameter indicates that AF requests to terminate the inference subscription, i.e. AF will not provide further notifications related to this subscription, with cause value.
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 11.4.5 Naf_Inference_Request service operation
| 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 (with parameters as defined in clause 6.1.3).
- Analytics Filter.
Outputs, Required: If the request is accepted, then VFL inference results, i.e. set of the tuple (Analytics ID, Analytics specific parameters). When the request is not accepted, an error response.
Outputs, Optional:
- Validity period.
- Confidence.
- Analytics Metadata Information.
- Analytics Accuracy Information.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 11.5 Naf_Training Service
| |
30701f0da928d70591b1088aae4273d2 | 23.288 | 11.5.1 General
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 11.5.2 Naf_Training_Subscribe service operation
| 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: See clause 6.2H.3 for parameters.
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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 11.5.3 Naf_Training_Unsubscribe service operation
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 11.5.4 Naf_Training_Notify service operation
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12 NEF Services to support network data analytics
| |
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.1 General
| 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
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.2 Nnef_VFLTraining Service
| |
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.2.1 General
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.2.2 Nnef_VFLTraining_Subscribe service operation
| 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.
- VFL correlation ID.
- Notification Target Address (+ Notification Correlation ID).
When updating a subscription:
- Subscription Correlation ID.
- For NWDAF as VFL client, external NWDAF ID.
Inputs, Optional: See clause 6.2H.3 for parameters.
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: First corresponding report (i.e. client intermediate training result) is included, if available and if consumer requested immediate reporting (see clause 4.15.1 of TS 23.502 [3]).
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.2.3 Nnef_VFLTraining_Unsubscribe service operation
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.2.4 Nnef_VFLTraining_Notify service operation
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.2.5 Nnef_VFLTraining_Request service operation
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.3 Nnef_VFLInference Service
| |
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.3.1 General
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.3.2 Nnef_VFLInference_Subscribe service operation
| 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.
- Data time window.
- Time when intermediate local result is needed.
- Dataset Statistical Properties.
- Analytics metadata request.
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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.3.3 Nnef_VFLInference_Unsubscribe service operation
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.3.4 Nnef_VFLInference_Notify service operation
| Service operation name: Nnef_VFLInference_Notify
Inputs, Required:
- Notification Correlation Information.
Inputs, Optional:
- Client intermediate results.
- Analytics Metadata Information.
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.3.5 Nnef_VFLInference_Request service operation
| 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.
- Data time window.
- Time when intermediate local result is needed.
- Dataset Statistical Properties.
- Analytics metadata request.
Outputs, Required: If the request is accepted, then client intermediate results. When the request is not accepted, an error response.
Outputs, Optional:
- Analytics Metadata Information.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.4 Nnef_VFLNFDiscovery Service
| |
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.4.1 General
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.4.2 Nnef_VFLNFDiscovery_NwdafDiscovery service operation
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.4.3 Nnef_VFLNFDiscovery_NwdafRelease service operation
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.5 Nnef_Inference Service
| |
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.5.1 General
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.5.2 Nnef_Inference_Subscribe service operation
| 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 (with parameters as defined in clause 6.1.3):
- Event Reporting parameters defined in Table 4.15.1-1 of TS 23.502 [3].
- 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: First corresponding inference report is included, if available and if analytics consumer requested immediate reporting (see clause 4.15.1 of TS 23.502 [3]).
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.5.3 Nnef_Inference_Unsubscribe service operation
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.5.4 Nnef_Inference_Notify service operation
| Inputs, Required:
- Notification Correlation Information.
Inputs, Optional:
- Inference results:
- Set of the tuple (Analytics ID, Analytics specific parameters): this parameter shall be present if output analytics are reported.
- Validity period.
- Confidence.
- Analytics Metadata Information.
- Analytics Accuracy Information.
- Revised waiting time.
- Termination Request: this parameter indicates that AF requests to terminate the inference subscription, i.e. AF will not provide further notifications related to this subscription, with cause value.
Outputs, Required: Operation execution result indication.
Outputs, Optional: None.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.5.5 Nnef_Inference_Request service operation
| 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 (with parameters as defined in clause 6.1.3).
- Analytics Filter.
Outputs, Required: If the request is accepted, then VFL inference results, i.e. set of the tuple (Analytics ID, Analytics specific parameters). When the request is not accepted, an error response.
Outputs, Optional:
- Validity period.
- Confidence.
- Analytics Metadata Information.
- Analytics Accuracy Information.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.6 Nnef_Training Service
| |
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.6.1 General
| Service Description: This service is provided by NEF AF acting on behalf of an untrusted 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.6.2 Nnef_Training_Subscribe service operation
| 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: See clause 6.2H.3 for parameters.
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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.6.3 Nnef_Training_Unsubscribe service operation
| 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.
|
30701f0da928d70591b1088aae4273d2 | 23.288 | 12.6.4 Nnef_Training_Notify service operation
| 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
2025-06
SP#108
SP-250464
1386
3
F
Enhancements on the input and output of QoS and Policy Assistance Analytics
19.3.0
2025-06
SP#108
SP-250461
1403
2
F
Clarifications on the definition of accuracy
19.3.0
2025-06
SP#108
SP-250461
1405
1
F
Clarifications on the file address related to ADRF
19.3.0
2025-06
SP#108
SP-250464
1411
3
F
Optimization of VFL triggers
19.3.0
2025-06
SP#108
SP-250464
1417
1
F
Alignment of existing mechanisms for accuracy generation impacted by VFL procedures
19.3.0
2025-06
SP#108
SP-250464
1421
2
F
Update triggering Case A and some corrections and Resolving ENs for VFL
19.3.0
2025-06
SP#108
SP-250464
1425
2
F
Parameters for vertical federated learning inference procedure
19.3.0
2025-06
SP#108
SP-250464
1429
4
F
Updates on VFL inference
19.3.0
2025-06
SP#108
SP-250464
1433
2
F
Editor's Note clean up for the VFL
19.3.0
2025-06
SP#108
SP-250461
1439
1
F
Attribute Level Change
19.3.0
2025-06
SP#108
SP-250464
1442
1
F
Clarification on Signalling Storm Analytics
19.3.0
2025-06
SP#108
SP-250461
1447
1
F
Correction on analytics feedback information
19.3.0
2025-06
SP#108
SP-250464
1450
2
F
Maintenance of VFL model training and inference with client intermediate results sharing between VFL clients
19.3.0
2025-06
SP#108
SP-250454
1453
1
A
Clarifications on accuracy monitoring procedure
19.3.0
2025-06
SP#108
SP-250464
1463
1
F
Typo correction in clause 6.2E.4 in TS 23.288
19.3.0
2025-06
SP#108
SP-250464
1464
2
F
Clarifications for Signalling Storm Analytics
19.3.0
2025-06
SP#108
SP-250464
1465
3
F
Clarification on data collection from SCP
19.3.0
2025-06
SP#108
SP-250461
1471
1
F
Correction on ML Model accuracy related information
19.3.0
2025-06
SP#108
SP-250461
1476
1
F
Optional Addition of last known UE Location
19.3.0
2025-09
SP#109
SP-250947
1415
3
F
Removal of requirements related to case 2b
19.4.0
2025-09
SP#109
SP-250947
1468
4
F
Correction on AIML_CN issues
19.4.0
2025-09
SP#109
SP-250942
1480
3
A
Corrections on ADRF related services
19.4.0
2025-09
SP#109
SP-250942
1482
-
A
Corrections on Location Accuracy Analytics and WLAN Analytics
19.4.0
2025-09
SP#109
SP-250947
1485
1
F
General maintenance of KI#1
19.4.0
2025-09
SP#109
SP-250942
1493
-
A
Corrections on ML model training service operation
19.4.0
2025-09
SP#109
SP-250953
1495
1
F
Corrections to Outputs of Relative Proximity Predictions
19.4.0
2025-09
SP#109
SP-250953
1496
1
F
Corrections to Movement Behaviour Analytics for Pre-flight Planning
19.4.0
2025-09
SP#109
SP-250942
1499
2
A
Correction on confidence of prediction
19.4.0
2025-12
SP#110
SP-251327
1426
5
F
Parameters for vertical federated learning inference procedure
19.5.0
2025-12
SP#110
SP-251327
1443
4
F
Clarification on VFL Server registration & discovery
19.5.0
2025-12
SP#110
SP-251327
1466
3
F
Correction on Feature ID used in NRF
19.5.0
2025-12
SP#110
SP-251327
1491
3
F
Further corrections on QoS and policy assistance analytics
19.5.0
2025-12
SP#110
SP-251327
1494
3
F
Correction on VFL preparation and VFL inference procedure
19.5.0
2025-12
SP#110
SP-251327
1500
3
F
Clarification made on VFL description in R19 TS 23.288
19.5.0
2025-12
SP#110
SP-251327
1502
3
F
Clarification on VFL client aggregation capability
19.5.0
2025-12
SP#110
SP-251327
1505
3
F
Clarifying Signalling Storm Analytics
19.5.0
2025-12
SP#110
SP-251327
1508
3
F
Alignment and correction on VFL training procedure
19.5.0
2025-12
SP#110
SP-251321
1511
2
F
Correction on timestamp of input data
19.5.0
2025-12
SP#110
SP-251321
1513
1
A
Corrections on Historical data and analytics via notification procedure
19.5.0
2025-12
SP#110
SP-251334
1515
1
F
Corrections on ADRF related features
19.5.0
2025-12
SP#110
SP-251327
1521
2
F
VFL clients removal during VFL training
19.5.0
2025-12
SP#110
SP-251327
1525
3
F
Correction on source of N6 delay
19.5.0
2025-12
SP#110
SP-251334
1535
2
F
Enhancing QoS Sustainability Analytics with QoS Flow Maintainability Threshold
19.5.0
2025-12
SP#110
SP-251327
1538
1
F
Updates of NWDAF discovery and ML model provisioning for LMF-based AI/ML Positioning
19.5.0
|
00c630369f4492b30b380be367f5dbf7 | 23.289 | 1 Scope
| 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], 3GPP TS 23.283 [23] and 3GPP TS 23.180 [27].
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.
|
00c630369f4492b30b380be367f5dbf7 | 23.289 | 2 References
| 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".
[27] 3GPP TS 23.180: "Mission critical services support in the Isolated Operation for Public Safety (IOPS) mode of operation"
[28] 3GPP TS 38.300: "NR; NR and NG-RAN Overall description; Stage-2."
|
00c630369f4492b30b380be367f5dbf7 | 23.289 | 3 Definitions of terms, symbols and abbreviations
| |
00c630369f4492b30b380be367f5dbf7 | 23.289 | 3.1 Terms
| 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].
Indirect path information: Consists of the path information and root relay in the form of User Info IDs of the MC capable 5G ProSe intermediate UE-to-Network relay(s) and the MC capable 5G ProSe multihop UE-to-Network relay, respectively, as defined in 3GPP TS 23.304 [17]. In case the remote MC service UE is directly connected to an MC capable 5G ProSe UE-to-Network relay, the indirect path information consists of the User Info ID of the MC capable 5G ProSe UE-to-Network relay under consideration.
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
|
00c630369f4492b30b380be367f5dbf7 | 23.289 | 3.2 Symbols
| Void.
|
00c630369f4492b30b380be367f5dbf7 | 23.289 | 3.3 Abbreviations
| 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
RSC Relay Service Code
RSRP Reference Signal Received Power
RSRQ Reference Signal Received Quality
SNPN Stand-alone Non-Public Network
SD-RSRP Sidelink Discovery RSRP
SL-RSRP Sidelink RSRP
NID Network Identifier
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4 MC system resource requirements
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.1 Multiple Access
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.1.1 General
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.1.2 Requirements
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.2 Session connectivity
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.2.1 General
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.2.2 Requirements
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3 QoS characteristics
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.1 General
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.2 QoS requirements for general purposes
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.3 QoS requirements for Mission Critical Push to Talk
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.3.1 General
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.3.2 5QI values for MCPTT
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.3.3 Use of priorities
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.4 QoS requirements for Mission Critical Video
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.4.1 General
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.4.2 5QI values for MCVideo
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.4.3 Use of priorities
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.5 QoS requirements for Mission Critical Data
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.5.1 General
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.5.2 5QI values for MCData
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.3.5.3 Use of priorities
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.4 Network Slicing
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.4.1 General
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.4.2 Requirements
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.5 Use of public and non-public networks
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.5.1 General
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.5.2 Requirements
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.6 Migration
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.6.1 General
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.6.2 Public network utilization
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.6.3 Non-Public network utilization
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.7 Architectural aspects of MC services using MBS
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.7.1 General
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.7.2 General on-network architecture for use of MBS by MC services
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.7.3 Specific instantiations of on-network architecture for use of MBS by MC services
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.7.3.1 Instantiation without optional entities and associated interfaces
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.7.3.2 Instantiation without MBSF / MBSTF and associated interfaces
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.7.3.3 Instantiation without NEF and associated interfaces
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.7.4 Service layer‑based interworking between eMBMS and MBS
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.7.5 Application layer based interworking between eMBMS and MBS
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.7.6 General architecture showcasing use of MBS by UE for MC services
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.8 Use of 5G ProSe UE-to-network relay
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.8.1 General
| 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.
5G ProSe UE-to-network relay service is either using one 5G ProSe UE-to-network relay MC service UE (as described in clause 4.8.2), or one 5G ProSe UE-to-network relay MC service UE together with 5G ProSe intermediate UE-to-network relay MC service UE(s) (as described in clause 4.8.3).
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.8.2 5G ProSe UE-to-network relay service requirements
| 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 ID, 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.8.3 5G ProSe multi-hop UE-to-network relay service requirements
| In order to enable 5G ProSe multi-hop UE-to-network relaying capabilities (either Layer-2 or Layer-3), the MC system provides the appropriate parameters and configurations to the MC service UE(s). As defined in 3GPP TS 23.304 [17], the parameters associated with 5G ProSe Layer-3 multi-hop UE-to-network relay are among others: User Info ID, ProSe Layer-2 Group ID and ProSe Group IP multicast address, RSC(s), UE-to-network relay indicator per RSC (to indicate whether the associated RSC is offering 5G ProSe Layer-2 or Layer-3 UE-to-network relay service), multi-hop indicator per RSC, and maximum number of hops supported per RSC.
NOTE: The RSC used for multi-hop service is different from the RSC used in clause 4.8.2.
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.9 EPS interworking
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.9.1 General
| 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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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.9.2 Requirements
| For MC services over a 5G system with EPS interworking, inter-system mobility between 5GC and EPC/E-UTRAN of MC service UEs shall be supported by the network based on the capabilities and procedures defined in 3GPP TS 23.501 [7], 3GPP TS 23.502 [10], and 3GPP TS 23.503 [9].
For the case that seamless session continuity is required for MC services, e.g. for MCPTT services, EPS interworking with N26 (interface between AMF in 5GC and MME in EPC) is required for inter-system change.
The MC system should be able to subscribe/unsubscribe to notification capabilities of specific events from the network related to EPS interworking. Thereby, the MC system can identify whether an MC service UE is registered on 5GS or EPS.
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.10 Use of 5G ProSe UE-to-UE relay
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.10.1 General
| The MC service shall support the capabilities for 5G ProSe UE-to-UE relay. For this matter, 5G ProSe Layer-2 and 5G ProSe Layer-3 UE-to-UE relaying techniques can be utilized, as described in 3GPP TS 23.304 [17].
A 5G ProSe UE-to-UE relay supporting MC service UE provides means of connectivity and relaying of MC traffic from a MC service UE to another MC service UE(s) via a MC UE Relay. For this matter, the 5G ProSe UE-to-UE Relay Discovery service allows the MC service remote UE to discover a potential UE-to-UE relay supporting MC service in its proximity as described in 3GPP TS 23.304 [17]. Upon its discovery, the 5G ProSe Direct UE-to-UE Relay Communication functionality is utilized to achieve communication to provide the MC service between MC UEs, relaying MC traffic via the UE-to-UE relay UE over the NR PC5 reference point.
5G ProSe UE-to-UE relay service is either using one 5G ProSe UE-to-UE relay MC service UE (as described in clause 4.10.2), or using multiple 5G ProSe UE-to-UE relay MC service UEs (as described in clause 4.10.3).
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.10.2 5G ProSe UE-to-UE relay service requirements
| In order to enable 5G ProSe UE-to-UE relaying capabilities – whether based on Layer-3 or Layer-2 UE-to-UE 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 ID, 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-UE relay service and related procedures within members of a certain MC service group.
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.10.3 5G ProSe multi-hop UE-to-UE relay service requirements
| In order to enable 5G ProSe Layer-3 multi-hop UE-to-UE relaying capabilities, 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: RSC(s) which can be associated to a certain MC service group, User Info ID, ProSe Layer-2 Group ID and ProSe Group IP multicast address, RSC(s), UE-to-UE relay layer indicator (indicates that the associated RSC is supporting 5G ProSe Layer-3 UE-to-UE relay service), multi-hop indicator per RSC, and maximum number of hops per RSC.
NOTE: The RSC used for multi-hop service is different from the RSC used in clause 4.10.2.
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.11 Support of the 5GS congestion information exposure using L4S
| Based on the request from the MC system, the 5G system can expose network congestion information on the media path between the MC service server and MC service UE to enable reacting accordingly, e.g., adjust the application layer bit rate at the media sender side.
The 5G System can support Explicit Congestion Notification (ECN) marking for Low Latency, Low Loss and Scalable Throughput (L4S) support as defined in 3GPP TS 23.501 [7], clause 5.37.3. When supported and enabled, the 5G System is applying ECN marking for L4S on a per QoS flow basis in the uplink and/or downlink direction and may be used for GBR and non-GBR QoS flows.
To support this feature on a service data flow, the MC service client and MC service server are capable of supporting the L4S handling including e.g., parsing the L4S ECN mark in the IP header, reporting the L4S feedback about downlink and/or uplink direction. The MC service server enables this feature by initiating the request for L4S marking towards the network (either directly towards PCF or indirectly via NEF).
Related procedures are specified in clause 7.7.
NOTE 1: The activation of ECN marking can also be triggered via the 5G core (SMF or PCF) based on either a dynamic or a predefined PCC rule, or dynamically upon the detection of L4S traffic in the IP header.
NOTE 2: The details related to MC service server and MC service UE upon reception of congestion information, e.g., including media handling, codec and bit rate negotiation are outside the scope of the current document.
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.12 Support of MC services over NTN
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 4.12.1 General
| The MC service UE should utilize satellite access to obtain MC services as specified in 3GPP TS 23.501 [7], 3GPP TS 23.502 [10] and 3GPP TS 23.503 [9].
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00c630369f4492b30b380be367f5dbf7 | 23.289 | 5 MC system functional model
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