Description
Application Data Analytics Enablement (ADAE) is a framework standardized by 3GPP to facilitate the consumption of network-generated analytics by external applications. It operates as a service capability within the 5G Core Network, specifically defined as a Network Exposure Function (NEF) service. The primary architectural principle involves an Application Function (AF) acting as a client that sends analytics subscription requests to the ADAE service, which is hosted by the NEF. The ADAE service then interfaces with various data sources within the network, such as the Network Data Analytics Function (NWDAF), Unified Data Repository (UDR), or other Network Functions (NFs), to collect, process, and deliver the requested analytics reports back to the AF.
The workflow begins with the AF sending a Nnef_AnalyticsExposure_Subscribe request message to the NEF, specifying the type of analytics needed (e.g., user-level mobility patterns, service experience analytics, network performance trends), the target user equipment (UE) group, and the reporting criteria (periodic or event-triggered). The NEF, acting as the ADAE service provider, authenticates and authorizes the AF request based on operator policies. It then translates the application-level analytics request into internal network procedures, potentially querying an NWDAF for the analytics computation or retrieving stored data from a UDR.
Key components in the ADAE architecture include the NEF (which hosts the ADAE service), the consuming AF, and the producer of analytics data (such as NWDAF). The interface between the AF and NEF for ADAE is defined as Nnef_AnalyticsExposure. The analytics data model is standardized, covering categories like UE mobility, communication patterns, and service experience, ensuring interoperability. The delivered analytics report contains insights like predicted UE movement, expected QoS sustainability, or abnormal service experience indicators, formatted according to 3GPP-defined data structures.
ADAE's role is to provide a secure, policy-controlled, and standardized channel for applications to leverage network intelligence without requiring direct, proprietary integrations with individual network functions. It enables use cases like crowd management, augmented reality optimization, and predictive service assurance by allowing applications to make data-driven decisions based on real-time or historical network analytics. The service supports both pull (request-response) and push (subscription-notification) models for data delivery, offering flexibility to application developers.
Purpose & Motivation
ADAE was created to address the growing demand from vertical industries and application providers to access valuable analytics derived from 5G network data. Prior to its standardization, applications had limited, non-standardized ways to obtain network insights, often relying on bilateral agreements or proprietary APIs that were not scalable, secure, or interoperable across different operator networks. This hindered the development of innovative services that could dynamically adapt based on network conditions or user behavior.
The motivation stems from the 5G vision of enabling network exposure and programmability. While NEF already exposed various network capabilities (like QoS control), there was a specific gap in exposing processed analytics, not just raw events or status. NWDAF was defined internally for network automation, but a standardized external interface for applications to consume these analytics was missing. ADAE fills this gap by defining a consistent service-based interface, data models, and authorization framework, allowing operators to monetize network data safely and enabling developers to build smarter applications.
It solves the problem of siloed network intelligence by providing a controlled funnel through which rich analytics—such as user mobility predictions, session aggregate bandwidth trends, or anomaly detection—can be securely shared with trusted third parties. This empowers new business models and enhances application performance, contributing to the overall 5G ecosystem of network-as-a-service and vertical industry support.
Classification
Detected Changes Across Releases
from 3GPP Change RequestsSpecific changes extracted from the „Change history“ tables of 3GPP specifications (46 CRs across 3 releases). Complements the general historical overview above with the evidence-based evolution of this function.
In Release 17, the ADAE function introduced procedures for supporting A-ADRF data storage and edge load analytics, as defined in TS 23.436. Furthermore, enhancements focused on making network exposure APIs more application-friendly, addressing gaps where parameters and service granularity were not easily understandable for developers of services like XR and IoT. This included work on designing APIs where consumers supply only required input parameters for specific application scenarios.
In Release 18, the ADAE function introduced new, specific analytics capabilities including UE-to-UE session performance analytics, VAL application performance analytics, slice-specific application performance analytics, location accuracy performance analytics, and slice usage pattern analytics. These enhancements expanded the data model and procedures for supporting A-ADRF data storage and edge load analytics. The updates aimed to make the APIs more application-oriented and easier to use for various verticals like V2X and UAS.
- UE-to-UE session performance analytics request TS 24.559CR0001
- Supported features indication in UE-to-UE session performance analytics TS 24.559CR0002
- VAL application performance API TS 29.549CR0184
- Slice-specific application performance API TS 29.549CR0186
- VAL performance analytics TS 29.549CR0212
- Slice-specific application performance analytics TS 29.549CR0214
+ 16 more changes
In Release 19, the ADAE function introduced several new analytics capabilities including Collision Detection Analytics and Location-related UE Group Analytics, along with specific API outputs for these and other services like Edge Load Analytics and Slice Performance Analytics. The release also expanded ADAE's scope with new analytics for UE RAT connectivity, satellite coverage availability, and Data Network (DN) energy analytics. Furthermore, ADAE was formally integrated as a service within the SEAL (Service Enabler Architecture Layer) architecture, enhancing its role in the 3GPP exposure ecosystem.
- Collision Detection Analytics TS 24.559CR0007
- Location-related UE Group Analytics TS 24.559CR0008
- Analytics output for the SS_ADAE_CollisionDetectionAnalytics API TS 29.549CR0358
- Analytics output for the SS_ADAE_LocationRelatedUeGroupAnalytics API TS 29.549CR0363
- Update with new TS for metaverse enablement services TS 29.549CR0375
- Analytics output for SS_ADAE_EdgeLoadAnalytics API TS 29.549CR0391
+ 16 more changes
Explore further
Broader topics and technologies where ADAE plays a role.
Defining Specifications
3GPP specifications that define or reference ADAE, with the latest known release. Sourced from the 3GPP document catalog — see methodology.
| Specification | Title | Release |
|---|---|---|
| TS 23.700 vk00 | XR Services Application Enablement Layer | Rel-20 |
| TS 24.559 vj41 | Application Data Analytics Enablement Services | Rel-19 |
| TS 24.560 vj00 | AIML Enablement (AIMLE) Services Stage 3 Protocol | Rel-19 |
| TS 29.549 vj40 | SEAL API Specification for Vertical Applications | Rel-19 |