Communications, Caching, and Computing for Mobile Virtual Reality: Modeling and Tradeoff

Virtual reality (VR) over wireless is emerging as an important use case of 5G networks. Fully-immersive VR experience requires the wireless delivery of huge data at ultra-low latency, thus leading to ultra-high transmission rate requirement for wireless communications. This challenge can be largely...

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Bibliographic Details
Published in:IEEE transactions on communications 2019-11, Vol.67 (11), p.7573-7586
Main Authors: Sun, Yaping, Chen, Zhiyong, Tao, Meixia, Liu, Hui
Format: Article
Language:English
Subjects:
Bandwidth
Bandwidths
Caching
Constraints
Edge computing
Electronic devices
low latency
Mobile computing
mobile edge computing
Optimization
Post-production processing
Power consumption
Servers
Three-dimensional displays
Tradeoffs
transmission rate
Transmission rate (communications)
Two dimensional displays
Videos
Virtual reality
wireless caching
Wireless communication
Wireless communications
Wireless networks
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Summary:Virtual reality (VR) over wireless is emerging as an important use case of 5G networks. Fully-immersive VR experience requires the wireless delivery of huge data at ultra-low latency, thus leading to ultra-high transmission rate requirement for wireless communications. This challenge can be largely addressed by the recent network architecture known as mobile edge computing (MEC) network, which enables caching and computing capabilities at the edge of wireless networks. This paper presents a novel MEC-based mobile VR delivery framework that is able to cache parts of the field of views (FOVs) in advance and compute certain post-processing procedures on demand at the mobile VR device. To minimize the average required transmission rate, we formulate the joint caching and computing optimization problem to determine which FOVs to cache, whether to cache them in 2D or 3D as well as which FOVs to compute at the mobile device under cache size, average power consumption as well as latency constraints. When FOVs are homogeneous, we obtain a closed-form expression for the optimal joint policy which reveals interesting communications-caching-computing tradeoffs. When FOVs are heterogeneous, we obtain a local optima of the problem by transforming it into a linearly constrained indefinite quadratic problem and then applying concave convex procedure. Numerical results demonstrate the proposed mobile VR delivery framework can significantly reduce communication bandwidth while meeting low latency requirement.
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2019.2920594