JOURNAL ARTICLE

QoE-Driven Resource Allocation Optimized for Uplink Delivery of Delay-Sensitive VR Video Over Cellular Network

Junchao YangJiangtao LuoDe MengJenq–Neng Hwang

Year: 2019 Journal:   IEEE Access Vol: 7 Pages: 60672-60683   Publisher: Institute of Electrical and Electronics Engineers

Abstract

Uploading virtual reality (VR) video over cellular networks is expected to boom in the near future, as general consumers could generate the high-quality VR videos with portable 360-degree cameras and are willing to share with others. Consequently, the concerns of uplink bandwidth and delay arose for current popular technology of tile-based VR video streaming, which requires high-quality video to transcode into multiple representations for further adaptive streaming. Motivated by this, we proposed a novel scheme for uplink delivery of tile-based VR video over cellular networks, in which encoding bit rate of each tile is determined by the uplink resource allocation (RA), and the quality of content (QoC) contribution of each tile and channel quality of user equipments (UEs) are jointly considered during RA. Moreover, the RA problem is formulated as a frequency and time dependent non-deterministic polynomial (NP)-hard problem. Furthermore, we propose three algorithms to explore solving the RA problem. The simulation results show that the proposed approximate convex algorithm with low-complexity can achieve higher utility, i.e., higher total quality of experience (QoE) for viewers.

Keywords:
Telecommunications link Computer science Resource allocation Computer network Cellular network Resource management (computing) Real-time computing

Metrics

17
Cited By
0.96
FWCI (Field Weighted Citation Impact)
27
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Telecommunications and Broadcasting Technologies
Physical Sciences →  Engineering →  Media Technology
Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
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