Video conferencing over 5G is increasingly prevalent, yet its Quality of Experience (QoE) often degrades under limited radio resources. This has two causes: 5G networks must serve many users, while interactive traffic requires careful handling. Motivated by the insight that different subflows within an interactive session have a disproportionate effect on QoE, we present the design and implementation of StreamGuard, a practical 5G architecture for subflow-level, QoE-aware prioritization. StreamGuard forms a closed control loop with three components: (1) a monitor in the Radio Access Network (RAN) that uses deep packet inspection to infer QoE and RAN state, (2) a controller that selects prioritization actions to balance QoE and fairness, and (3) a marking module that applies these decisions by marking packets to steer subflows into appropriate priority queues. StreamGuard further shapes application behaviors via mechanisms including selective subflow dropping and probe-based rate control, to align application behavior with radio constraints. Implemented in a real 5G testbed, StreamGuard achieves a superior QoE-fairness tradeoff compared to vanilla 5G and prior state-of-the-art approaches, improving QoE by up to 70% at comparable background throughput or preserving up to 2x higher background throughput at similar QoE.

翻译：在5G网络中进行视频会议日益普遍，然而其体验质量在无线资源受限时常常下降。这有两个原因：5G网络必须服务大量用户，同时交互式流量需要谨慎处理。基于交互会话中不同子流对体验质量具有非对称影响的洞察，我们提出了StreamGuard的设计与实现——一种实用的、面向子流级别体验质量感知优先级划分的5G架构。StreamGuard通过三个组件构成闭环控制：（1）无线接入网中的监控模块，利用深度包检测推断体验质量与无线接入网状态；（2）控制器，选择优先级划分策略以平衡体验质量与公平性；（3）标记模块，通过为数据包添加标记驱动子流进入相应优先级队列来执行决策。StreamGuard进一步通过选择性子流丢弃与基于探测的速率控制等机制塑造应用行为，使应用行为与无线资源约束对齐。在真实5G测试平台上的部署验证表明，相较于原始5G及现有最优方法，StreamGuard实现了更优的体验质量-公平性折中，在可比背景吞吐量下提升高达70%的体验质量，或在相似体验质量下保持高达2倍的背景吞吐量。