基于移动边缘计算的虚拟现实压缩与传输系统

doi:10.11959/j.issn.1000-436x.2020076

通信学报 ›› 2020, Vol. 41 ›› Issue (4): 45-53.doi: 10.11959/j.issn.1000-436x.2020076

所属专题：边缘计算

• 专题：边缘计算关键技术 • 上一篇下一篇

基于移动边缘计算的虚拟现实压缩与传输系统

谭彬¹,赵嵩源²,吴俊³,张文茹⁴

¹ 井冈山大学电子与信息工程学院，江西吉安 343009
² 同济大学电子与信息工程学院，上海 201804
³ 复旦大学计算机科学与技术学院，上海 200433
⁴ 复旦大学计算机科学与技术学院，上海 200433；4.广东省新一代通信与网络创新研究院，广东广州 510070

修回日期:2020-03-16 出版日期:2020-04-25 发布日期:2020-04-30
作者简介:谭彬（1982- ），女，湖南常宁人，博士，井冈山大学副教授，主要研究方向为无线视频通信理论及关键技术、信源信道联合编码及边缘计算等。|赵嵩源（1996- ），男，天津人，同济大学硕士生，主要研究方向为边缘计算、无线通信等。|吴俊（1971- ），男，博士，复旦大学教授、博士生导师，主要研究方向为无线网络关键技术、人工智能与机器学习、嵌入式系统软硬件技术等|张文茹（1975- ），女，河北唐山人，广东省新一代通信与网络创新研究院高级工程师，主要研究方向为无线通信技术、网络体系架构等
基金资助:
国家自然科学基金资助项目(61762053);国家自然科学基金资助项目(61601128);国家自然科学基金资助项目(61831018);国家自然科学基金资助项目(61631017)

Virtual reality compressing and transmitting system based on mobile edge computing

Bin TAN¹,Songyuan ZHAO²,Jun WU³,Wenru ZHANG⁴

¹ College of Electronics and Information Engineering,Jinggangshan University,Ji’an 343009,China
² College of Electronics and Information Engineering,Tongji University,Shanghai 201804,China
³ School of Computer and Technology,Fudan University,Shanghai 200433,China
⁴ School of Computer and Technology,Fudan University,Shanghai 200433,China 4.Guangdong Communications ＆Networks Institute,Guangzhou 510070,China

Revised:2020-03-16 Online:2020-04-25 Published:2020-04-30
Supported by:
The National Natural Science Foundation of China(61762053);The National Natural Science Foundation of China(61601128);The National Natural Science Foundation of China(61831018);The National Natural Science Foundation of China(61631017)

摘要/Abstract

摘要：

针对基于云服务的虚拟现实对数据传输速率的高要求以及对传输时延的敏感性问题，提出并设计了基于移动边缘计算技术的云VR系统方案，主要包括基于视点的VR处理和混合数模传输优化。首先采用基于金字塔投影的用户视点感知动态推流方法实现基于视点的VR处理；然后引入混合数模技术对传输进行优化改进，并给出了启发式的资源分配优化算法；最后在长期演进（LTE）系统的基础上改造基站协议栈，融入移动边缘计算技术，实现了完整的移动边缘云VR系统。实验结果表明，与已有方案相比，所提方案能够实现更加稳健高效的传输，达到更好的VR用户体验。

关键词: 虚拟现实, 移动边缘计算, 混合数模

Abstract:

In order to solve the problem of the high requirements of data transmission rate and sensitivity to transmission delay in virtual reality (VR) based on cloud services,a Cloud VR system with MEC (mobile edge computing) was proposed,mainly including viewpoint-based VR processing and HDA (hybrid digital-analog) transmission optimization.Firstly,a dynamic streaming method based on user viewpoint and pyramid projection was used to implement a complete edge cloud VR system.Then,HDA transmission was introduced to optimize the transmission,and a heuristic algorithm for resource allocation was given.Finally,the base station protocol stack was transformed,and the MEC was integrated into the LTE (long term evolution) system to implement a complete mobile edge cloud VR system.Experimental results demonstrate that the proposed scheme has good robustness and efficient transmission by comparing with the existing schemes.

Key words: virtual reality, mobile edge computing, hybrid digital-analog

中图分类号:

TN929.5

谭彬,赵嵩源,吴俊,张文茹. 基于移动边缘计算的虚拟现实压缩与传输系统[J]. 通信学报, 2020, 41(4): 45-53.

Bin TAN,Songyuan ZHAO,Jun WU,Wenru ZHANG. Virtual reality compressing and transmitting system based on mobile edge computing[J]. Journal on Communications, 2020, 41(4): 45-53.

图/表 5

参考文献 15

[1]	华为 iLab. Cloud VR解决方案白皮书[R].(2018-09)[2020-01-06]
	Huawei iLab. Cloud VR solution white paper[R].(2018-09)[2020-01-06].
[2]	刘洁, 王庆扬, 林奕琳 . 5G 网络中的移动 VR 应用[J]. 电信科学, 2018,34(10): 149-155.
	LIU J , WANG Q Y , LIN Y L . Mobile VR application in 5G network[J]. Telecommunications Science, 2018,34(10): 149-155.
[3]	左旭彤, 王莫为, 崔勇 . 低时延网络:架构,关键场景与研究展望[J]. 通信学报, 2019,40(8): 22-35.
	ZUO X T , WANG M W , CUI Y . Low-latency networking:architecture,key scenarios and research prospect[J]. Journal on Communications, 2019,40(8): 22-35.
[4]	WU J , WU J , CUI H ,et al. DAC-Mobi:data-assisted communications of mobile images with cloud computing support[J]. IEEE Transactions on Multimedia, 2016,18(5): 893-904.
[5]	WU J , LIU D , HUANG X L ,et al. DaC-RAN:a data-assisted cloud radio access network for visual communications[J]. IEEE Wireless Communications, 2015,22(3): 130-136.
[6]	TAN B , LU J , WU J ,et al. Toward a network slice design for ultra high definition video broadcasting in 5G[J]. IEEE Wireless Communications, 2018,25(4): 88-94.
[7]	JAKUBCZAK S , KATABI D . A cross-layer design for scalable mobile video[C]// Proceedings of the 17th Annual International Conference on Mobile Computing and Networking. New York:ACM Press, 2011: 289-300.
[8]	HOSSEINI M , SWAMINATHAN V . Adaptive 360 VR video streaming based on MPEG-DASH SRD[C]// 2016 IEEE International Symposium on Multimedia. Piscataway:IEEE Press, 2017: 407-408.
[9]	HYEON S K , SANG B N , SANG G C ,et al. HLS-based 360 VR using spatial segmented adaptive streaming[C]// IEEE International Conference on Consumer Electronics. Piscataway:IEEE Press, 2018: 1-4.
[10]	华为 iLab. 面向 Cloud VR 的承载网络白皮书[R].(2017-10)[2020-01-06].
	Huawei iLab. Cloud VR-oriented bearer network white paper[R].(2017-10)[2020-01-06].
[11]	LIU Z , ISHIHARA S , CUI Y ,et al. JET:joint source and channel coding for error resilient virtual reality video wireless transmission[J]. Signal Processing, 2018,147: 154-162.
[12]	FENG J , WU Y , ZHAI G ,et al. An algorithm for transmitting VR video based on adaptive modulation[C]// IEEE/CIC International Conference on Communications in China. Piscataway:IEEE Press, 2019: 443-448.
[13]	LEE K H , PETERSEN D . Optimal linear coding for vector channels[J]. IEEE Transactions on Communications, 1976,24(12): 1283-1290.
[14]	TAN B , CUI H , WU J ,et al. An optimal resource allocation for superposition coding-based hybrid digital–analog system[J]. IEEE Internet of Things Journal, 2017,4(4): 945-956.
[15]	FENG H , WU J , GONG X . SOUP:Advanced SDR platform for 5G communication[C]// IEEE/CIC International Conference on Communications in China. Piscataway:IEEE Press, 2017: 1-5.

基于移动边缘计算的虚拟现实压缩与传输系统

Virtual reality compressing and transmitting system based on mobile edge computing

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