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Reliability Enhancement for VR Delivery in Mobile-Edge Empowered Dual-Connectivity $μ$Wave-mmWave HetNets
arXiv - CS - Networking and Internet Architecture Pub Date : 2020-11-20 , DOI: arxiv-2011.10293
Zhuojia Gu, Hancheng Lu, Peilin Hong, Yongdong Zhang

The reliability of current virtual reality (VR) delivery is low due to the limited resources on VR head-mounted displays (HMDs) and the transmission rate bottleneck of sub-6 GHz ($\mu$Wave) networks. In this paper, we propose a dual-connectivity $\mu$Wave-mmWave heterogeneous network architecture empowered by mobile edge capability. The core idea of the proposed architecture is to utilize the complementary advantages of $\mu$Wave links and mmWave links to conduct a collaborative edge resource design, which aims to improve the reliability of VR delivery. From the perspective of stochastic geometry, we analyze the reliability of VR delivery and theoretically demonstrate that $\mu$Wave links can be used to enhance the reliability of VR delivery despite the large mmWave bandwidth. Based on our analytical work, we formulate a joint caching and computing optimization problem with the goal to maximize the reliability of VR delivery. By analyzing the coupling caching and computing strategies at HMDs, $\mu$Wave and mmWave base stations (BSs), we further transform the problem into a multiple-choice multi-dimension knapsack problem. A best-first branch and bound algorithm and a difference of convex programming algorithm are proposed to obtain the optimal and sub-optimal solution, respectively. Numerical results demonstrate the performance improvement using the proposed algorithms, and reveal that caching more monocular videos at $\mu$Wave BSs and more stereoscopic videos at mmWave BSs can improve the VR delivery reliability efficiently.

中文翻译:

增强了移动边缘支持的双连接中VR交付的可靠性$μ$ Wave-mmWave HetNets

由于VR头戴式显示器(HMD)上的资源有限以及6 GHz以下($ muWave)网络的传输速率瓶颈,当前虚拟现实(VR)交付的可靠性较低。在本文中,我们提出了一种具有移动边缘功能的双连接性$ \ mu $ Wave-mmWave异构网络体系结构。所提出的体系结构的核心思想是利用$ muWave链接和mmWave链接的互补优势来进行协作边缘资源设计,目的是提高VR交付的可靠性。从随机几何的角度,我们分析了VR交付的可靠性,并从理论上证明了$ \ mu $ Wave链接可用于增强VR交付的可靠性,尽管mmWave带宽很大。根据我们的分析工作,我们制定了一个联合缓存和计算优化问题,旨在最大程度地提高VR交付的可靠性。通过分析HMD,$ muWave和mmWave基站(BS)的耦合缓存和计算策略,我们将问题进一步转换为多选多维背包问题。提出了最佳优先分支定界算法和凸规划算法的差分,分别获得最优解和次优解。数值结果证明了使用所提出算法的性能提高,并揭示了在$ \ mu $ Wave BS处缓存更多的单目视频和在mmWave BS处缓存更多的立体视频可以有效地提高VR交付的可靠性。通过分析HMD,$ muWave和mmWave基站(BS)的耦合缓存和计算策略,我们将问题进一步转换为多选多维背包问题。提出了最佳优先分支定界算法和凸规划算法的差分,分别获得最优解和次优解。数值结果证明了使用所提出算法的性能提高,并揭示了在$ \ mu $ Wave BS处缓存更多的单目视频和在mmWave BS处缓存更多的立体视频可以有效地提高VR交付的可靠性。通过分析HMD,$ muWave和mmWave基站(BS)的耦合缓存和计算策略,我们将问题进一步转换为多选多维背包问题。提出了最佳优先分支定界算法和凸规划算法的差分,分别获得最优解和次优解。数值结果证明了使用所提出算法的性能提高,并揭示了在$ \ mu $ Wave BS处缓存更多的单目视频和在mmWave BS处缓存更多的立体视频可以有效地提高VR交付的可靠性。提出了最佳优先分支定界算法和凸规划算法的差分,分别获得最优解和次优解。数值结果证明了使用所提出算法的性能提高,并揭示了在$ \ mu $ Wave BS处缓存更多的单目视频和在mmWave BS处缓存更多的立体视频可以有效地提高VR交付的可靠性。提出了最佳优先分支定界算法和凸规划算法的差分,分别获得最优解和次优解。数值结果证明了使用所提出算法的性能提高,并揭示了在$ \ mu $ Wave BS处缓存更多的单目视频和在mmWave BS处缓存更多的立体视频可以有效地提高VR交付的可靠性。
更新日期:2020-11-23
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