Scalability of Wi-Fi Performance in Virtual Reality Scenarios.

Area of Science:

• Computer Science
• Electrical Engineering
• Wireless Communications

Background:

• Virtual Reality (VR) adoption in Wi-Fi networks is rapidly increasing.
• VR applications demand stringent Quality of Service (QoS) with low latency and high throughput.
• Wi-Fi networks face challenges in meeting VR QoS due to channel fading and interference.

Purpose of the Study:

• To conduct a comprehensive scalability study of Wi-Fi performance in multi-user VR scenarios.
• To investigate if enhanced Access Point (AP) capabilities, specifically Multi-User MIMO (MU-MIMO), can support dense VR deployments.
• To identify bottlenecks limiting Wi-Fi performance scaling in VR environments.

Main Methods:

• Developed a high-fidelity simulation framework using ns-3 to estimate network capacity for VR traffic.
• Evaluated the impact of AP and STA antenna count, MU-MIMO scheduling, channel sounding period, and channel conditions.
• Analyzed performance scaling with increased AP antenna count.

Main Results:

• Wi-Fi performance scalability in multi-user VR scenarios is not linear.
• Doubling AP antennas from 8 to 16 resulted in only a 35% capacity gain under typical conditions.
• Identified key bottlenecks preventing indefinite performance scaling with more AP antennas.

Conclusions:

• Simply increasing AP antennas, even with MU-MIMO, is insufficient for supporting dense VR deployments.
• Understanding and addressing identified bottlenecks is crucial for designing next-generation Wi-Fi systems for the Metaverse and immersive VR.
• The study provides critical insights for optimizing Wi-Fi network design for future VR applications.