UAV-Assisted Edge Computing and Streaming for Wireless Virtual Reality: Analysis, Algorithm Design, and Performance Guarantees
Document Type
Article
Publication Date
3-1-2022
Abstract
Emerging virtual reality (VR) applications require high data rate transmission and low end-to-end latency, which has become one of the main challenges for future wireless networks. Unmanned aerial vehicle (UAV) mounted base stations and computing facilities can be used to provide better wireless connectivity and computing services to edge VR users to meet their computing needs and reduce the end-to-end latency. We propose a novel UAV assisted mobile edge computing (MEC) network to enable high-quality mobile 360-degree video VR applications by leveraging UAVs to provide the required communication and computing needs. Then, we formulate the joint UAV placement, MEC and radio resource allocation, and 360-degree video content layer assignment (UAV-MV) problem, which aims to select the allocation of computing and communications resources and the location of the UAVs such that the delivered quality of experience (QoE) is maximized across the mobile VR users, given various system constraints. We show that the problem is NP-hard, and decompose it into three lower-complexity subproblems that we solve sequentially. We design an approximation algorithm with performance guarantees that solves the UAV-MV problem based on the solutions to the three subproblems. Our simulation results show that the average QoE enabled by the proposed algorithm is 15% and 90% greater relative to two competitive reference methods.
Identifier
85124756934 (Scopus)
Publication Title
IEEE Transactions on Vehicular Technology
External Full Text Location
https://doi.org/10.1109/TVT.2022.3142169
e-ISSN
19399359
ISSN
00189545
First Page
3267
Last Page
3275
Issue
3
Volume
71
Grant
CCF-1528030
Fund Ref
National Science Foundation
Recommended Citation
Zhang, Liang and Chakareski, Jacob, "UAV-Assisted Edge Computing and Streaming for Wireless Virtual Reality: Analysis, Algorithm Design, and Performance Guarantees" (2022). Faculty Publications. 3092.
https://digitalcommons.njit.edu/fac_pubs/3092