Evaluating Wi-Fi Performance for VR Streaming: A Study on Realistic HEVC Video Traffic

TL;DR

This study evaluates Wi-Fi network capacity for VR streaming with realistic HEVC video traffic, revealing how coding techniques and user load impact latency and throughput in high-demand scenarios.

Contribution

The paper introduces an emulation framework for realistic VR traffic and analyzes Wi-Fi performance, highlighting the effectiveness of Intra-refresh coding in supporting multiple VR users.

Findings

IR coding reduces latency variability

Wi-Fi supports up to 4 VR users at 100 Mbps

Channel saturation occurs beyond 4 users

Abstract

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.