# 3GPP Technical Document Summary: CR 0607 to TS 26.114

## Document Information
- **CR Number**: 0607
- **Specification**: TS 26.114 v19.2.0
- **Category**: B (addition of feature)
- **Release**: Rel-20
- **Work Item**: AIML_IMS-MED
- **Source**: Samsung Electronics Iberia SA

## Purpose and Rationale

This Change Request introduces stage 3 specifications for AI/ML processing capabilities in IMS services. The CR addresses the missing technical specifications for AI/ML data delivery and signaling mechanisms required to support AI/ML-enhanced IMS services in Release 20.

## Main Technical Contributions

### 1. References, Terms, and Abbreviations (Clauses 2, 3.1, 3.3)

Updates to include AI/ML-specific terminology, definitions, and abbreviations relevant to IMS services. Specific content marked as **Editor's Notes** for future completion.

### 2. New Annex AC: AI/ML Assisted Media Processing for MTSI

A comprehensive new normative annex is introduced covering all aspects of AI/ML integration with MTSI.

#### AC.1 Introduction
Provides introductory material on AI/ML capabilities in IMS services.

#### AC.2 Terminal Architecture
Defines updates to terminal architecture to accommodate:
- Inference engine
- AI/ML models
- Intermediate data handling

#### AC.3 End-to-End Reference Architecture
Potential updates to the end-to-end reference architecture for AI/ML support. Notes indicate possible liaison requirements with SA2.

### 3. AI/ML Call Flows (AC.4)

#### AC.4.1 AI/ML Model Delivery for Device Inferencing

Detailed 15-step call flow for AI/ML model delivery and execution:

**Key Steps:**
1. **Session Establishment**: MMTel service establishment
2. **Bootstrap Data Channel (BDC) Setup**: Established between UE and MF per TS 23.228
3. **Application Discovery**: UE requests application list via HTTP over BDC
4. **Application List Creation**: DCSF generates user-specific DC application list with metadata including:
   - Generic app information (description, ID, URL)
   - AI-specific information (AI feature tags, task descriptions)
5. **Application Selection**: User selects app based on AI service descriptions
6-9. **Application Download**: Selected AI application downloaded from DCSF via MF to UE, including AI task metadata (task manifest)
10. **Task Selection**: User presented with AI task list and selects desired tasks
11. **Model Request**: Selected tasks and models communicated to MF via:
   - BDC: HTTP GET with task/model URLs
   - ADC: AI Model Selection Request with model URNs
12. **Model Retrieval**: MF fetches AI models from either:
   - 12a: DCAR via DCSF
   - 12b: DC AS
13. **Model Download**: UE downloads AI models from MF via:
   - BDC: HTTP response with AI models as resource
   - ADC: AI Model Selection Response with model data
14. **Inference Execution**: Tasks executed on UE
15. **Task Reselection**: User/UE may reselect tasks during session using received metadata

**Open Issues Identified:**
- Whether MF needs to understand AI task semantics (FFS)
- Application types that can be handled
- Large model handling mechanisms

#### AC.4.2 Network Inferencing
Placeholder for network-based inference scenarios.

#### AC.4.3 Split Inferencing
Placeholder for distributed inference scenarios across UE and network.

### 4. AI/ML Capabilities (AC.5)

Defines capabilities and requirements for:
- **AC.5.1 UE Capabilities**: Device-side AI/ML requirements
- **AC.5.2 Network Capabilities**: Network-side AI/ML requirements

### 5. AI/ML Formats (AC.6)

Specification of formats for:
- AI/ML models
- Intermediate data

### 6. AI/ML Metadata (AC.7)

Definition of necessary metadata structures for AI/ML operations, including task manifests referenced in the call flows.

### 7. Negotiation and Signaling (AC.8)

Procedures for:
- Model delivery negotiation
- Inferencing coordination
- General AI/ML media processing signaling

### 8. Data Channel Transport (AC.9)

Specification of AI/ML data transport mechanisms:
- What data to transport over BDC (Bootstrap Data Channel)
- What data to transport over ADC (Application Data Channel)
- Transport procedures and protocols

## Key Technical Entities

- **MF**: Media Function
- **DCSF**: Data Channel Selection Function
- **DCAR**: Data Channel Application Repository
- **DC AS**: Data Channel Application Server
- **BDC**: Bootstrap Data Channel
- **ADC**: Application Data Channel

## Implementation Status

Most technical content is marked with **Editor's Notes**, indicating this is a skeleton CR establishing the structure for future detailed specifications. The most complete section is AC.4.1 (AI/ML model delivery for device inferencing), which provides a concrete call flow example.