基于开源5G网络的FWA Over-the-Top内容交付中的客观视频质量评估
Objective Video Quality Assessment in FWA-Based Over-the-Top Content Delivery Across Open Source 5G Networks
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中文总结 AI 辅助
本研究在开源5G FWA测试平台上，通过客观QoE指标评估传输模式、调制和负载对4K视频质量的影响，证明MIMO优于SISO，为UHD传输优化提供实证依据。
中文摘要 AI 辅助
本文在基于5G的固定无线接入（FWA）网络中进行了全面的实验性视频质量评估，利用了一个真实的开源5G网络测试平台。针对超高清（UHD）视频传输的关键需求，本研究系统性地调查了传输模式（SISO和MIMO）、调制方案（64-QAM和256-QAM）以及网络负载（一至五个用户）对网络吞吐量和感知视频质量的影响。与基于模拟的方法不同，我们的方法将自动化流媒体活动与通过MPEG-DASH传输的4K视频流计算得出的客观全参考体验质量（QoE）指标（PSNR、SSIM和VMAF）相结合，实现了网络性能与用户体验之间的帧级相关性分析。主要发现表明，MIMO始终优于SISO，即使在用户需求增加的情况下也能维持更高的吞吐量和更优的视觉质量。具体而言，采用256-QAM的MIMO在五个并发用户时保持了VMAF分数高于视觉无损阈值，而SISO配置则经历了显著的性能下降。这些结果为空间分集和高阶调制在确保FWA上可靠UHD视频传输中的关键作用提供了经验证据。所提出的可复现的详细质量评估框架为未来5G FWA部署的优化提供了宝贵见解，有助于在Open RAN环境中对高质量视频服务的实际理解和部署策略。
英文摘要
This paper presents a comprehensive experimental video quality assessment in 5G-based Fixed Wireless Access (FWA) networks, leveraging a real open source 5G network testbed. Addressing the critical need for robust UHD video delivery, the study systematically investigates the impact of transmission modes (SISO and MIMO), modulation schemes (64-QAM and 256-QAM), and network load (one to five users) on both network throughput and perceived video quality. Unlike simulation-based approaches, our methodology integrates automated streaming campaigns with objective full-reference Quality of Experience (QoE) metrics (PSNR, ssim, and VMAF) computed from 4K video streams delivered via MPEG-DASH, enabling frame-level correlation between network performance and user experience. Key findings demonstrate that MIMO consistently outperforms SISO, sustaining higher throughput and superior visual quality even under increasing user demand. Specifically, MIMO with 256-QAM maintained VMAF scores above the visually lossless threshold with five concurrent users, while SISO configurations experienced significant degradation. These results provide empirical evidence for the critical role of spatial diversity and higher-order modulation in ensuring reliable UHD video delivery over FWA. The proposed reproducible framework for detailed quality assessment offers valuable insights for future optimization of 5G FWA deployments, contributing to the practical understanding and deployment strategies for high-quality video services in Open RAN environments.
