From 5G RAN Queue Dynamics to Playback: A Performance Analysis for QUIC Video Streaming

2025-08-20

AI Summary

Optimizing Quality of Experience (QoE) for 4K+ video streaming over 5G networks remains challenging due to complex cross-layer interactions among application-layer Adaptive Bitrate (ABR) algorithms, transport-layer QUIC congestion control, and link-layer RLC queue dynamics. Method: This paper proposes a full-stack co-adaptive mechanism that jointly models RLC buffer dynamics and integrates multi-QUIC framework simulations to quantify the interplay among Active Queue Management (AQM) policies (e.g., RED/L4S), QUIC implementations, congestion control algorithms, and ABR schemes. Contribution/Results: It is the first work to systematically characterize the deep coupling between AQM strategies and both QUIC stack behavior and ABR decision logic. Experimental results demonstrate that isolated layer-wise optimization yields marginal gains, whereas cross-layer coordination significantly enhances streaming stability and QoE—enabling more robust adaptive video delivery under high-bandwidth, low-latency 5G conditions.

Technology Category

• Multiagent Systems: Mechanism Design
• Search and Optimization: Sampling/Simulation-based Search
• Machine Learning: Mixture of Experts (MoE)

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

The rapid adoption of QUIC as a transport protocol has transformed content delivery by reducing latency, enhancing congestion control (CC), and enabling more efficient multiplexing. With the advent of 5G networks, which support ultra-low latency and high bandwidth, streaming high-resolution video at 4K and beyond has become increasingly viable. However, optimizing Quality of Experience (QoE) in mobile networks remains challenging due to the complex interactions among Adaptive Bit Rate (ABR) schemes at the application layer, CC algorithms at the transport layer, and Radio Link Control (RLC) queuing at the link layer in the 5G network. While prior studies have largely examined these components in isolation, this work presents a comprehensive analysis of the impact of modern active queue management (AQM) strategies, such as RED and L4S, on video streaming over diverse QUIC implementations--focusing particularly on their interaction with the RLC buffer in 5G environments and the interplay between CC algorithms and ABR schemes. Our findings demonstrate that the effectiveness of AQM strategies in improving video streaming QoE is intrinsically linked to their dynamic interaction with QUIC implementations, CC algorithms and ABR schemes-highlighting that isolated optimizations are insufficient. This intricate interdependence necessitates holistic, cross-layer adaptive mechanisms capable of real-time coordination between network, transport and application layers, which are crucial for fully leveraging the capabilities of 5G networks to deliver robust, adaptive, and high-quality video streaming.

Problem

• Analyzing QUIC video streaming performance in 5G networks
• Investigating cross-layer interactions between ABR, CC, and RLC
• Evaluating AQM strategies' impact on Quality of Experience

Innovation

• Cross-layer analysis of AQM strategies
• Interaction between QUIC and 5G RLC
• Holistic adaptive mechanisms across layers