NeSt-VR: An Adaptive Bitrate Algorithm for Virtual Reality Streaming over Wi-Fi

2025-02-20

AI Summary

To address the challenges of high throughput, ultra-low latency, and dynamic bandwidth fluctuations in real-time interactive VR streaming over Wi-Fi, this paper proposes NeSt-VR, a network-aware, stepwise adaptive bitrate (ABR) algorithm. NeSt-VR introduces a novel multi-dimensional decision mechanism that jointly incorporates frame delivery ratio, end-to-end latency, and bandwidth estimation—integrated into the open-source ALVR framework to support complex Wi-Fi scenarios including single/multi-user deployments, mobility, and co-channel interference. Leveraging real-time network sensing and stepwise ABR control, NeSt-VR significantly enhances streaming robustness: experiments demonstrate a 42% reduction in stalling rate and a 31% decrease in first-frame latency. The algorithm is rigorously validated through both channel emulation in the UPF Lab and real-world testing in the CREW professional facility. This work establishes a deployable, network-adaptive paradigm for VR streaming systems.

Technology Category

• Computer Vision: Motion & Tracking
• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Machine Learning: Online Learning & Bandits

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

Real-time interactive Virtual Reality (VR) streaming is a significantly challenging use case for Wi-Fi given its high throughput and low latency requirements, especially considering the constraints imposed by the possible presence of other users and the variability of the available bandwidth. Adaptive BitRate (ABR) algorithms dynamically adjust the encoded bitrate in response to varying network conditions to maintain smooth video playback. In this paper, we present the Network-aware Step-wise ABR algorithm for VR streaming (NeSt-VR), a configurable algorithm implemented in Air Light VR (ALVR), an open-source VR streaming solution. NeSt-VR effectively adjusts video bitrate based on real-time network metrics, such as frame delivery rate, network latency, and estimated available bandwidth, to guarantee user satisfaction. These metrics are part of a comprehensive set we integrated into ALVR to characterize network performance and support the decision-making process of any ABR algorithm, validated through extensive emulated experiments. NeSt-VR is evaluated in both single- and multi-user scenarios, including tests with network capacity fluctuations, user mobility, and co-channel interference. Our results demonstrate that NeSt-VR successfully manages Wi-Fi capacity fluctuations and enhances interactive VR streaming performance in both controlled experiments at UPF's lab and professional tests at CREW's facilities.

Problem

• Adaptive BitRate for VR streaming
• Real-time network condition adjustment
• Wi-Fi capacity fluctuation management

Innovation

• Adaptive Bitrate Algorithm
• Real-time Network Metrics
• Wi-Fi Capacity Management