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：5G视频会议日益普及，但其体验质量在有限无线资源下常出现劣化，其原因有二：5G网络需服务大量用户，且交互式流量需精细处理。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，我们提出并实现了StreamGuard——一种实用的子流级、体验质量感知优先级排序5G架构。StreamGuard构建了包含三个组件的闭环控制环路：（1）无线接入网中的监测器，通过深度包检测推断体验质量与无线接入网状态；（2）控制器，选择优先级分配策略以平衡体验质量与公平性；（3）标记模块，通过数据包标记将子流导向对应优先级队列以执行决策。StreamGuard进一步通过选择性子流丢弃与探针式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测试平台上的实现表明，相比标准5G及现有最优方案，StreamGuard实现了更优的体验质量-公平性权衡：在可比背景吞吐量条件下提升体验质量达70%，或在相似体验质量下保持高达2倍的背景吞吐量。