Summary of 3GPP Technical Document S4-260161

Document Overview

This is a pCR (proposed Change Request) to 3GPP TR 26.870 introducing Embodied Video Internet (EVI) as a new use case for 6G Media studies. The document proposes adding a new clause 6.1 to the technical report, focusing on media requirements for embodied AI systems (robots, UAVs) that actively capture and process video in dynamic environments.

Main Technical Contributions

1. Introduction to Embodied Video Internet (Clause 6.1.1)

Core Concept:
- Defines Embodied AI as integration of AI into physical systems enabling real-world interaction
- Introduces paradigm shift from static/passive recording to dynamic/mobile/embodied sensing
- Distinguishes between:
- Old Paradigm: Fixed cameras with limited FOV and constrained coverage
- New Paradigm: Mobile devices (robots, UAVs) as "mobile eyes and limbs" actively exploring environments

Definition:
- Embodied Video: Use of 6G networks enabling intelligent agents to capture, process, and react to visual information in real-time within dynamic environments

2. SA1 Use Case Analysis (Clause 6.1.2)

Extracts and summarizes four relevant use cases from TR 22.870:

Use Case 6.28: Network-assisted Video-based AI Inference Task Offloading

Technical Requirements:
- Multi-camera systems (6-8 cameras) with concurrent multi-modal data streams (video, point clouds)
- Three operational scenarios defined:
- Scenario I: 6x 1080p @ 15Hz → 20 Mbps
- Scenario II: 4x 1080p + 2x 4K @ 15/30Hz → 60 Mbps
- Scenario III: 2x 1080p + 4x 4K @ 15/30Hz → 100 Mbps
- Alternative: 4x 1080p + 2x 4K @ 60Hz
- E2E RTT: 100-300ms
- Compression ratio: 240:1 assumed
- Distributed AI inference tasks: multi-modal perception, 3D digital twin modeling, trajectory planning

Media Requirements:
- AI codec with error-tolerant capabilities (Grace method)
- Real-time processing of high-resolution video and multi-modality data
- High uplink data rate and low latency

Use Case 6.19: AI-based Video Analysis

Application Context:
- Real-time infrastructure inspection (utility poles, guardrails)
- Security surveillance
- Network offloading for resource-intensive video analysis

Media Requirements:
- Native integration of video analysis algorithms (object recognition, anomaly detection)
- Low latency communication

Use Case 6.48: Service Robot for Power Grid

System Architecture:
- Embedded controllers for motion control (walking, grasping) - fast response
- Network offloading for computing-intensive tasks (large AI models, control command generation)

KPI Requirements:

| Traffic Type | Message Size | Transfer Interval | Data Rate | E2E Latency | Reliability |
|--------------|--------------|-------------------|-----------|-------------|-------------|
| UL sensor data | 1250-12500 Bytes | 10 ms | 1-10 Mbps | 100-150 ms | 99.99% |
| UL LiDAR | 345600 Bytes | 100 ms | 27.6 Mbps | 100-150 ms | 99.99% |
| DL Control command | 625-12500 Bytes | 50 ms | 0.1-2 Mbps | - | - |

Technical Notes:
- LiDAR: 10 Hz frame rate, 28800 points/frame, 12 bytes/point
- E2E latency breakdown: ~40ms communication + ~100ms AI inference

Media Requirements:
- Real-time processing of multi-modality data (video, audio, point clouds, LiDAR)

Use Case 6.11: Intelligent UAV Swarms

Operational Concept:
- UAVs with built-in AI capabilities for enhanced perception, decision-making, control
- Swarm deployment for full area coverage and complex task execution
- Network offloading during local computing overload (e.g., HD 3D map generation)

Media Requirements:
- Real-time processing of multi-modality data from multiple UAVs

3. External Evidence - UAV Inspection Use Cases (Clause 6.1.3)

Table 2.1.3-1: UAV Inspection Requirements

| Use Case | Video Resolution | Data Rate | E2E Latency | Reliability |
|----------|------------------|-----------|-------------|-------------|
| Traffic surveillance | 1080p | ≥5 Mbps | <100 ms | >99.99% |
| Traffic surveillance | 4K | >25 Mbps | <100 ms | >99.99% |
| Urban management | 1080p | ≥5 Mbps | 20-100 ms | - |
| Event security | 1K | ≥5 Mbps | ≤10 ms | - |
| Event security | 4K | ≥25 Mbps | ≤10 ms | - |
| Rural inspections | 4K | ≥25 Mbps | <100 ms | - |

Table 2.1.3-2: UAV 3D Mapping Requirements

| Use Case | Data Type | Data Rate | E2E Latency |
|----------|-----------|-----------|-------------|
| Topographic surveying | High-res video, LiDAR | ≥30 Mbps | 20-100 ms |
| Reconstruction | 4K video | ≥50 Mbps | 20-100 ms |
| Mine monitoring | Video, LiDAR, sensor | ≥30 Mbps | 20-100 ms |
| Rural governance | High-res video, LiDAR | ≥30 Mbps | 20-100 ms |

4. Consolidated Requirements for 6G Media (Clause 6.1.4)

Four Key Requirements Identified:

1. AI Codec Technology
2. Error-tolerant capabilities within frames

3. Grace method for better UX vs. traditional codecs

4. AI-native Video Protocol

5. New protocol design for AI-driven video systems

6. Low-latency Video Transmission

7. Critical for real-time embodied AI operations

8. QoE Model for Performance Measurement

9. User-centric parameters:
   • Multi-stream data types
   • Data quality
   • Accuracy and reliability of feedback results
10. Network-centric parameters:
    • Network delivery speed
    • Latency
    • End-to-end packet loss
    • Network usage

Technical Significance

This pCR establishes foundational requirements for supporting embodied AI systems in 6G media, addressing:
- Multi-modal concurrent data streaming
- Real-time AI inference offloading
- High-reliability, low-latency video transmission
- Novel QoE metrics for embodied video applications
- AI-native codec and protocol requirements

The document bridges SA1 service requirements with SA4 media specifications, providing concrete KPIs and use case evidence for the FS_6G_MED study.