实测显示，Wi-Fi支持4个并发VR用户，关键靠编码优化降延迟。
Evaluating Wi-Fi Performance for VR Streaming: A Study on Realistic HEVC Video Traffic
- 用真实HEVC视频流模拟VR场景，测试不同设置下的网络表现。
- 开启帧内刷新后，延迟波动降低，4个用户共享100Mbps恒定码率不卡顿。
- 适合研究VR网络优化或部署的工程师参考。
基于云的虚拟现实（VR）流媒体对802.11网络提出高吞吐与低延迟的双重挑战。当多个VR用户共享同一Wi-Fi网络时，上行与下行流量易迅速饱和信道。本文研究了802.11网络在不同帧率、码率、编码设置及用户数量下支持真实VR流媒体工作的能力。我们构建了一个仿真框架，重现Air Light VR（ALVR）运行状态，将真实HEVC视频流量输入802.11仿真模型。研究发现，帧内刷新（Intra-refresh, IR）编码能有效降低延迟波动，提升服务质量，在恒定码率100 Mbps条件下，可支持最多4个并发VR用户，直至信道饱和。
原文摘要 · Abstract (English)
Cloud-based Virtual Reality (VR) streaming presents significant challenges for 802.11 networks due to its high throughput and low latency requirements. When multiple VR users share a Wi-Fi network, the resulting uplink and downlink traffic can quickly saturate the channel. This paper investigates the capacity of 802.11 networks for supporting realistic VR streaming workloads across varying frame rates, bitrates, codec settings, and numbers of users. We develop an emulation framework that reproduces Air Light VR (ALVR) operation, where real HEVC video traffic is fed into an 802.11 simulation model. Our findings explore Wi-Fi's performance anomaly and demonstrate that Intra-refresh (IR) coding effectively reduces latency variability and improves QoS, supporting up to 4 concurrent VR users with Constant Bitrate (CBR) 100 Mbps before the channel is saturated.
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