Collaborative Research: NeTS: Immersi- Fi: A Multi-Connectivity LiFi-Based Platform for Mobile Immersive Systems: Modeling, Algorithms, and Testbed

Virtual Reality (VR) and Augmented Reality (AR) technologies and applications have become popular in recent years by enabling immersive user experiences in entertainment, healthcare, and education. However, high-quality VR/AR applications require tens of Gigabits per second data rates with low latency to enable desirable quality of experience for users. Existing wireless technologies, such as WiFi, cannot meet these requirements. This project aims to develop novel directed light-fidelity (LiFi) networks for high‑throughput VR/VR applications, which significantly improve the signal power delivery efficiency compared to current LiFi systems based on homogeneous-illumination visible light. Furthermore, this project will involve graduate and undergraduate students in interdisciplinary research and introduce STEM fields to high school students. The project develops hardware and algorithms for directed-LiFi networking with near-infrared light beamforming and adaptive VR/AR streaming. The research effort is organized into three inter-related thrusts. First, hardware subsystems along with control algorithms are developed to enable fast adaptive directed-LiFi beamforming, steering, and user position tracking. Second, multi-user resource allocation and scheduling schemes are developed to support integrated LiFi and WiFi dual connectivity. Third, application layer protocols and algorithms are developed to allocate available communication and computational resources across the wireless edge and VR/AR clients for efficient 360-degree video streaming. Moreover, a multi-connectivity directed-LiFi testbed is developed to facilitate experimental exploration and validation of adaptive and scalable multipath VR/AR streaming. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.