Challenges in Transporting Sensing Data with Media Over QUIC rev 03 lands on the IETF Datatracker
This document proposes leveraging Media Over QUIC (MOQ) to address the challenges of transmitting large-scale, real-time sensing data in 6G networks. By building on QUIC's low-latency and multiplexing capabilities, MOQ offers a flexible and efficient transport mechanism tailored to the dynamic and high-throughput requirements of 6G environments. The approach focuses on enabling protocol adaptability across diverse application scenarios such as autonomous driving, smart cities, and industrial IoT, while ensuring efficient data fragmentation, secure and anonymous transmission, and end-to-end QoS awareness. Through information-aware endpoints and optimized data delivery mechanisms, this solution supports scalable, reliable, and intelligent sensing data distribution in next-generation wireless networks. It is also available to other types of 6G System Data [3GPP.22.870] besides sensing data, e.g., AI data, positioning data.
Draft Snapshot
- Draft:
draft-yue-moq-transporting-sensing-data - Revision: 03
- Last updated: 2025-10-19
- Source: IETF Datatracker
Summary
This document proposes leveraging Media Over QUIC (MOQ) to address the challenges of transmitting large-scale, real-time sensing data in 6G networks. By building on QUIC's low-latency and multiplexing capabilities, MOQ offers a flexible and efficient transport mechanism tailored to the dynamic and high-throughput requirements of 6G environments. The approach focuses on enabling protocol adaptability across diverse application scenarios such as autonomous driving, smart cities, and industrial IoT, while ensuring efficient data fragmentation, secure and anonymous transmission, and end-to-end QoS awareness. Through information-aware endpoints and optimized data delivery mechanisms, this solution supports scalable, reliable, and intelligent sensing data distribution in next-generation wireless networks. It is also available to other types of 6G System Data [3GPP.22.870] besides sensing data, e.g., AI data, positioning data.
Analysis
This draft is directly relevant to the MOQ ecosystem and worth tracking because it reflects current protocol work or adjacent implementation guidance from the IETF process.
Abstract
This document proposes leveraging Media Over QUIC (MOQ) to address the challenges of transmitting large-scale, real-time sensing data in 6G networks. By building on QUIC's low-latency and multiplexing capabilities, MOQ offers a flexible and efficient transport mechanism tailored to the dynamic and high-throughput requirements of 6G environments. The approach focuses on enabling protocol adaptability across diverse application scenarios such as autonomous driving, smart cities, and industrial IoT, while ensuring efficient data fragmentation, secure and anonymous transmission, and end-to-end QoS awareness. Through information-aware endpoints and optimized data delivery mechanisms, this solution supports scalable, reliable, and intelligent sensing data distribution in next-generation wireless networks. It is also available to other types of 6G System Data [3GPP.22.870] besides sensing data, e.g., AI data, positioning data.