End-to-End Performance of Video Streaming With MPEG-DASH Over Satellite 5G IAB Networks

2026-04-17

AI Summary

This study addresses the degradation of Quality of Experience (QoE) in MPEG-DASH video streaming over integrated 5G Integrated Access and Backhaul (IAB) networks that incorporate Low Earth Orbit (LEO) satellites, where high latency and throughput fluctuations pose significant challenges. The authors develop an end-to-end simulation framework based on ns-3 to systematically evaluate, for the first time, the impact of TCP and QUIC protocols—each paired with various congestion control algorithms including CUBIC, NewReno, and BBR—on video QoE. Experimental results demonstrate that the QUIC-BBR combination achieves superior performance in terms of playback duration, rebuffering frequency, and latency, significantly outperforming other protocol-algorithm pairings. This configuration strikes an optimal balance among throughput, delay, playback continuity, and fairness, offering an effective optimization pathway for video delivery in satellite-integrated internet architectures.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Machine Learning: Mixture of Experts (MoE)
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Security and Privacy: Large-scale security measurements

Abstract

We present an end-to-end performance evaluation of MPEG-DASH video streaming over a Low-Earth Orbit (LEO) satellite-based 5G Integrated Access and Backhaul (IAB) network. Our objective is to investigate how modern transport protocols and congestion control algorithms affect adaptive video delivery in an integrated satellite-terrestrial network (ISTN), where latency, throughput variation, and playback continuity jointly shape the user Quality-of-Experience (QoE). We implement a simulation framework in ns-3 by adapting open-source modules for the 5G radio access network, LEOS backhaul, transport layer protocols, and MPEG-DASH application behavior. Within this framework, TCP and QUIC are evaluated with multiple congestion control algorithms, including CUBIC, NewReno, and BBR. Performance is assessed using application-level and transport-level metrics, including playback duration, interruption duration, stall count, playback bitrate, throughput, latency, and fairness. The results show that no single configuration is uniformly optimal across all metrics. However, clear tradeoffs are observed among throughput, latency, playback continuity, and fairness. In particular, QUIC-BBR provides the most balanced overall behavior from a streaming QoE perspective, combining adequate playback duration with fewer interruptions and substantially lower latency than other alternatives. These findings highlight the importance of jointly considering transport design and congestion control when evaluating adaptive video streaming over ISTNs.

Problem

• MPEG-DASH
• Satellite 5G IAB
• Adaptive Video Streaming
• Quality-of-Experience
• Integrated Satellite-Terrestrial Network

Innovation

• MPEG-DASH
• Satellite 5G IAB
• QUIC-BBR
• Integrated Satellite-Terrestrial Network
• QoE