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TS 23.288
Architecture enhancements for 5GS
to support Network Data Analytics Services

3GPP‑Page   ETSI‑search   eToC↓   LoFT↓   CONTENT →
V19.1.0 (Wzip)  2024/12  367 p.
V18.8.0 (PDF)  2024/12  329 p.
V17.12.0  2024/06  211 p.
V16.12.0  2022/09  69 p.
Rapporteur:
Mr. Wu, Xiaobo
HuaWei Technologies Co., Ltd

essential Table of Contents for  TS 23.288  Word version:  19.1.0

each title, in the "available" or "not available yet" area, links to the equivalent title in the CONTENT
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List of Figures and Tables

Figure 4.2.0-1Data Collection architecture from any 5GC NF
Figure 4.2.0-1aData Collection architecture using Data Collection Coordination
Figure 4.2.0-2Network Data Analytics Exposure architecture
Figure 4.2.0-2aNetwork Data Analytics Exposure architecture using Data Collection Coordination
Figure 4.2.0-3Trained ML Model Provisioning architecture
Figure 4.2.1-1Data storage architecture for Analytics and Collected Data
Figure 4.3-1Roaming Architecture to exchange Input Data or Data Analytics between VPLMN and HPLMN
Table 5A.2-1NF Services consumed by DCCF or NWDAF to determine which NF instances are serving a UE
Figure 5A.3.1-1Data Delivery via DCCF
Figure 5A.3.2-1Data Delivery via a Messaging Framework
Table 5A.4-1Examples of Event Parameter Names, Parameter values
Figure 6.1.1.1-1Network data analytics Subscribe/unsubscribe
Figure 6.1.1.2-1Procedure for analytics subscribe/unsubscribe by AFs via NEF
Figure 6.1.2.1-1Network data analytics Request
Figure 6.1.2.2-1Procedure for analytics request by AFs via NEF
Figure 6.1.4.2-1Network data analytics subscription via DCCF
Figure 6.1.4.3-1Historical Analytics Exposure via DCCF
Figure 6.1.4.4-1Network data analytics subscription via DCCF
Figure 6.1.4.5-1Historical Analytics Exposure via Messaging Framework
Figure 6.1.5.2-1Procedure for analytics exposure from HPLMN to VPLMN
Figure 6.1.5.3-1Procedure for analytics exposure from VPLMN to HPLMN
Figure 6.1A.3.1-1Procedure for analytics aggregation
Figure 6.1A.3.2-1Procedure for analytics aggregation without provision of Area of Interest
Figure 6.1B.2.1-1Analytics context transfer initiated by target NWDAF selected by the NWDAF service consumer
Figure 6.1B.2.2-1Analytics subscription transfer initiated by source NWDAF
Figure 6.1B.2.3-1Prepared analytics subscription transfer
Figure 6.1B.3-1Analytics Context Transfer
Figure 6.1C.2-1NWDAF registration in UDM
Figure 6.1C.3-1NWDAF de-registration from UDM
Table 6.2.2.1-1NF Services consumed by NWDAF for data collection
Table 6.2.2.1-2NF Services consumed by NWDAF to determine which NF instances are serving a UE
Table 6.2.2.1-3NF Services consumed by NWDAF to determine which NF instances are matching analytics filters
Figure 6.2.2.2-1Event Exposure Subscribe/unsubscribe for NFs
Figure 6.2.2.3-1Data Collection from AF via NEF
Figure 6.2.3.2-1Data collection from OAM performance data file report management service
Table 6.2.4-1Correlation Information
Figure 6.2.5.2-1Procedure for time coordination across multiple NWDAFs
Table 6.2.6.0-1NF Services for the enhanced data collection procedures
Figure 6.2.6.2-1Data Collection from NWDAF via Data Management Service
Figure 6.2.6.3.2-1Data Collection via DCCF
Figure 6.2.6.3.3-1Historical Data Collection via DCCF
Figure 6.2.6.3.4-1Data Collection via Messaging Framework
Figure 6.2.6.3.5-1Historical Data Collection via Messaging Framework
Figure 6.2.6.3.6-1Procedure for the NWDAF or ADRF register data profile to DCCF
Figure 6.2.6.3.7-1Procedure for DCCF relocation initiated by consumer
Figure 6.2.6.3.8-1Procedure for DCCF relocation initiated by DCCF
Figure 6.2.7.2-1Procedure for muting event notification
Figure 6.2.8.2.3-1Data Collection Procedure from UE
Figure 6.2.8.2.4.2-1AF in trusted domain correlates UE data collection and NWDAF request
Figure 6.2.8.2.4.3-1AF in untrusted domain correlates UE data collection and NWDAF request
Figure 6.2.8.2.4.4-1NWDAF correlates UE data collection and NWDAF request
Figure 6.2.8.2.4.5-1AF correlates UE data collection and NWDAF request when there is NAT between UE and AF
Figure 6.2.10-1data collection by H-RE-NWDAF from V-RE-NWDAF for outbound roaming users
Figure 6.2.11-1Data Collection by V-RE-NWDAF from H-RE-NWDAF for inbound roaming users
Figure 6.2.12.2-1Data collection using LCS
Figure 6.2.13.2NWDAF containing AnLF-based untrusted AF data source rating
Figure 6.2.14.2-1Procedure for analytics collection from MDAF
Figure 6.2A.1-1ML Model for analytics subscribe/unsubscribe
Figure 6.2A.3-1ML Model Request
Table 6.2B-1DataSetTag attribute
Figure 6.2B.2-1Historical Data and Analytics storage
Figure 6.2B.3-1Historical Data and Analytics Storage via Notifications
Figure 6.2B.4-1Data Removal from an ADRF
Figure 6.2B.5-1ML Model Storage in ADRF
Figure 6.2B.6-1ML Model removal from ADRF
Figure 6.2B.7-1Procedure for ML Model(s) retrieval from ADRF
Figure 6.2C.2.1-1Registration and Discovery procedure for Federated Learning
Figure 6.2C.2.2-1General procedure for Federated Learning among Multiple NWDAF
Figure 6.2C.2.3-1Procedure of FL Server NWDAF reselects FL Client NWDAF(s), FL Client NWDAF(s) Join or Leave Federated Learning Process Dynamically in Federated Learning execution phase
Figure 6.2D.2-1Analytics Accuracy Information Subscribe
Figure 6.2D.3-1Analytics Accuracy Information Request
Figure 6.2E.2-1Procedure for MTLF-based ML Model Accuracy Monitoring
Figure 6.2E.3.2-1Procedure for ML Model monitoring registration
Figure 6.2E.3.3-1Procedure for monitoring the analytics accuracy of an ML Model
Figure 6.2F.1-1Procedure for ML Model Training subscribe/unsubscribe
Figure 6.2F.3-1Procedure for ML Model Training Information Request
Figure 6.2H.2.1.1-1Registration and Discovery procedure for Vertical Federated Learning when NWDAF is acting as VFL server and NWDAF(s) and/or AF(s) are the VFL clients
Figure 6.2H.2.1.2-1Registration and Discovery procedure for Vertical Federated Learning when AF is acting as VFL server and NWDAF(s) are the VFL clients
Figure 6.2H.2.2.1-1Preparation procedure for Vertical Federated Learning when NWDAF is the VFL Server
Figure 6.2H.2.2.2-1Preparation procedure for Vertical Federated Learning when untrusted AF is the VFL Server
Figure 6.2H.2.3.1-1Training procedure for Vertical Federated Learning when NWDAF is acting as VFL server
Figure 6.2H.2.3.2-1Training procedure for Vertical Federated Learning when untrusted AF is acting as VFL server
Figure 6.2H.2.4.1-1Inference procedure for vertical federated learning when NWDAF is acting as VFL server
Figure 6.2H.2.4.2-1Inference procedure for vertical federated learning when untrusted AF is acting as VFL server
Table 6.3.2A-1OAM Input data for slice load analytics
Table 6.3.2A-25GC NF Input data for slice load analytics
Table 6.3.3A-1Network Slice instance load statistics
Table 6.3.3A-2Network Slice load statistics
Table 6.3.3A-3Network Slice instance load predictions
Table 6.3.3A-4Network Slice load predictions
Figure 6.3.4-1Network Slice load analytics provided by NWDAF
Table 6.4.1-1Analytics Filter Information related to the observed service experience
Table 6.4.2-1Service Data from AF related to the observed service experience
Table 6.4.2-1aPerformance Data from AF
Table 6.4.2-1bQoE measurements from OAM related to specific service type
Table 6.4.2-2QoS flow level Network Data from 5GC NF related to the QoS profile assigned for a particular service (identified by an Application Id or IP filter information)
Table 6.4.2-3UE level Network Data from OAM related to the QoS profile
Table 6.4.2-4UE level Network Data from 5G NF related to the Service Experience
Table 6.4.2-5Data collection from MDAS/MDAF of service experience and energy saving state analysis
Table 6.4.3-1Service Experience statistics
Table 6.4.3-2Service Experience predictions
Figure 6.4.4-1Procedure for NWDAF providing Service Experience for an Application
Figure 6.4.5-1Procedure for NWDAF providing Service Experience for a UE or a group of UEs in a Network Slice
Figure 6.4.6-1Procedure for NWDAF providing Service Experience for an application for a UE or a group of UEs
Table 6.5.2-1Data collected by NWDAF for NF load analytics
Table 6.5.2-2Data collected by NWDAF for UPF load analytics
Table 6.5.2-3MDT input data for UE
Table 6.5.2-4Per UE attribute to be collected and processed by the AF
Table 6.5.2-5AF input data to the NWDAF for Collective Behaviour of UEs
Table 6.5.3-1NF load statistics
Table 6.5.3-2NF load predictions
Figure 6.5.4-1NF load analytics provided by NWDAF
Table 6.6.2-1Load and Performance information collected by NWDAF
Table 6.6.2-2Number of UEs in Area of Interest information collected by NWDAF
Table 6.6.3-1Network performance statistics
Table 6.6.3-2Network performance predictions
Figure 6.6.4-1Procedure for subscription to network performance analytics
Table 6.7.2.2-1UE Mobility information collected from 5GC
Table 6.7.2.2-2Service Data from AF related to UE mobility
Table 6.7.2.3-1UE mobility statistics
Table 6.7.2.3-2UE mobility predictions
Figure 6.7.2.4-1UE mobility analytics provided to an Analytics Service Consumer
Table 6.7.3.2-1Service Data from 5GC related to UE communication
Table 6.7.3.3-1UE Communication Statistics
Table 6.7.3.3-2UE Communication Predictions
Figure 6.7.3.4-1Procedure for UE communication analytics
Figure 6.7.4.4.1-1NWDAF assisted expected UE behavioural analytics procedure
Table 6.7.5.1-1Relation between expected analytics type and Exception IDs
Table 6.7.5.1-2Description of Expected UE Behaviour parameters per Exception ID
Table 6.7.5.2-1Exceptions information from AF
Table 6.7.5.3-1Abnormal behaviour statistics
Table 6.7.5.3-2Abnormal behaviour predictions
Table 6.7.5.3-3Examples of additional measurements and NF actions for risk solving
Figure 6.7.5.4-1Procedure for NWDAF assisted misused or hijacked UEs identification
Table 6.8.2-1Data Collected from the NF and OAM related to User Data Congestion Analytics
Table 6.8.2-2Data Collected from the UPF or from the AF related to User Data Congestion Analytics
Table 6.8.3-1User Data Congestion statistics
Table 6.8.3-2User Data Congestion predictions
Figure 6.8.4.1-1Procedure for one-time or continuous reporting of analytics for congestion in a geographic area
Figure 6.8.4.2-1Procedure for one-time or continuous reporting of analytics for congestion for a specific UE
Table 6.9.2-1Data collection for "QoS Sustainability" analytics
Table 6.9.2-2UE level data collection for "QoS Sustainability" analytics with fine granularity
Table 6.9.2-3Data collection for QoS Sustainability analytics at GTP level
Table 6.9.3-1"QoS Sustainability" statistics
Table 6.9.3-2"QoS Sustainability" predictions
Figure 6.9.4.1-1"QoS Sustainability" analytics provided by NWDAF in a coarse granularity area
Figure 6.9.4.2-1Procedure for "QoS Sustainability" analytics in a fine granularity area
Table 6.10.2-1Location based UE transactions dispersion information collected from serving AMF
Table 6.10.2-2UE transactions dispersion information collected from serving SMF
Table 6.10.2-3UE Data volume dispersion information collected from the AF
Table 6.10.2-4UE data volume dispersion collected from the AF
Table 6.10.2-5UE data volume dispersion collected from serving UPF
Table 6.10.2-6UE data volume dispersion collected from serving UPF
Table 6.10.2-7Slice based UE transactions dispersion information collected from serving AMF
Table 6.10.2-8Slice based UE transactions dispersion information collected from serving SMF
Table 6.10.3.1-1Data volume dispersion statistics bound by location
Table 6.10.3.1-2Data volume dispersion prediction bound by location
Table 6.10.3.1-3Data volume dispersion statistics bound by slice
Table 6.10.3.1-4Data volume dispersion prediction bound by slice
Table 6.10.3.1-5Data volume dispersion statistics bound by slice (for any UE)
Table 6.10.3.1-6Data volume dispersion prediction bound by slice (for any UE)
Table 6.10.3.2-1Transactions dispersion statistics bound by location
Table 6.10.3.2-2Transactions dispersion prediction bound by location
Table 6.10.3.2-3Transactions dispersion statistics bound by slice
Table 6.10.3.2-4Transactions dispersion prediction bound by slice
Figure 6.10.4-1UE Dispersion Analytics provided to an NF or AF
Table 6.11.2-1Data collected by NWDAF for WLAN performance analytics
Table 6.11.3-1WLAN performance statistics
Table 6.11.3-2WLAN performance predictions
Figure 6.11.4-1Procedure for WLAN performance analytics
Table 6.12.2-1Data collected by NWDAF for SMCCE analytics
Table 6.12.3-1SMCCE statistics
Figure 6.12.4-1Procedure for Session Management Congestion Control Experience Analytics
Table 6.13.2-1Packet drop and/or packet delay measurement per QFI or GTP level
Table 6.13.2-2The information related to PDU Session established
Table 6.13.2-3Data collection from MDAS/MDAF of end-to-end latency analysis
Table 6.13.3-1Redundant Transmission Experience statistics
Table 6.13.3-2Redundant Transmission Experience predictions
Figure 6.13.4.1-1Redundant Transmission Experience analytics provided to an NF
Table 6.14.1-1Analytics Filter Information related to DN Performance Analytics
Table 6.14.2-1Performance Data from AF
Table 6.14.3-1DN service performance statistics
Table 6.14.3-2DN service performance predictions
Figure 6.14.4-1Procedure for NWDAF providing DN Performance analytics for an Application
Table 6.16.2-1Input data to detect known application from NFs
Table 6.16.3-1PFD Determination statistics
Figure 6.16.4-1A procedure for NWDAF-assisted PFD Determination
Table 6.17.2-1Data Collected by NWDAF for Location Accuracy Analytics
Table 6.17.3-1Location Accuracy statistics
Table 6.17.3-2Location Accuracy predictions
Figure 6.17.4-1Location accuracy analytics retrieval
Table 6.18.2-1Input data from OAM related to E2E data volume transfer time
Table 6.18.2-2Service Data from 5GC NFs for E2E data volume transfer time analytics
Table 6.18.2-3Service Data from AF for E2E data volume transfer time analytics
Table 6.18.3-1E2E data volume transfer time statistics
Table 6.18.3-2E2E data volume transfer time predictions
Figure 6.18.4-1Procedure for E2E data volume transfer time analytics
Table 6.19.2-1OAM input data for relative proximity analytics
Table 6.19.2-2Proximity related input data collected via DCAF/NEF
Table 6.19.2-3Proximity related input data from 5GC/AF
Table 6.19.3-1Relative proximity statistics
Table 6.19.3-2Relative proximity predictions
Figure 6.19.4-1Procedure for NWDAF providing relative proximity analytics
Table 6.20.2-1Collected PDU Session User Plane Traffic Information
Table 6.20.3-1PDU Session traffic statistics
Figure 6.20.4-1NWDAF providing PDU Session traffic analytics
Table 6.21.2-1Data collection by NWDAF for "movement behaviour" analytics
Table 6.21.3-1movement behaviour statistics
Table 6.21.3-2movement behaviour predictions
Figure 6.21.4-1"Movement Behaviour" analytics provided by NWDAF
Table 6.22.2-1UE related Context Data collection
Table 6.22.2-2NF Context Data collection
Table 6.22.2-3NF Specific Data collection
Table 6.22.2-4Application activation time information
Table 6.22.2-5Data collection from NRF/OAM
Table 6.22.2-6Data collection from MDAF/MDAS of control plane congestion analysis
Table 6.22.3-1Signalling storm statistics
Table 6.22.3-2Signalling storm predictions
Table 6.22.3-3Example mechanisms to mitigate and prevent the signalling storm
Figure 6.22.4-1Procedure for NWDAF-assisted Network Signalling Storm Mitigation and Prevention
Table 6.23.2-1Input data from 5GC NF related to QoS and policy assistance information
Table 6.23.3-1QoS and Policy Assistance predictions
Figure 6.23.4-1Procedure for QoS and Policy Assistance Analytics
Table 7.1-1NF services provided by NWDAF
Table 7.1-2Analytics information provided by NWDAF
Table 8.1-1NF services provided by DCCF
Table 9.1-1NF services provided by MFAF
Table 10.1-1NF services provided by ADRF

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