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

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.

An Open Framework for Analyzing and Modeling XR Network Traffic

“…For this reason, a lot of effort has been devoted to creating network solutions for the maximization of the quality of the delivered content. In [27], for example, the authors proposed a scheme for uplink delivery of tile-based VR video over cellular networks. In particular, they formulate a resource allocation problem as a frequency and time-dependent non-deterministic polynomial NP-hard problem, and propose three distinct algorithms to solve it.…”

CMU-VP: Cooperative Multicast and Unicast With Viewport Prediction for VR Video Streaming in 5G H-CRAN

“…Consequently, the efficiency of transmission with short chunks is low because of ineffective compression and heavy cost of data synchronization. An efficient User-Generated Content (UGC) VR video transmission scheme over cellular network is represented in our previous work [25], in which only one representation of each tile is generated for uploading based on optimization of uplink resource allocation under the consideration of quality of content (QoC) contribution, then directly transmitted to viewer without transcoding.…”

“…With determined x v,t , for each viewer, the unicast and multicast schedule problem can be derived into two independent sub-problems P2 and P3. While the similar problem has been studied in our previous work [25], in which we adopted the greedy approach to solve this type of problem. Therefore, the problem P1 is finally solved by applying the greedy approach, and the Algorithm 1 summarizes the details of our approach, which is given as following:…”

“…s.t. (9), ( 10), (11) The sub-problem P4 is a convex problem, which can be solved efficiently by optimization toolbox or greedy algorithm in our previous study [25].…”

Layered Projection-Based Quality Assessment of 3D Point Clouds

“…Depending on the capturing device, those formats can correspond to holograms [1], light fields [2], or point cloud (PC) [3], etc. Among these, PCs denote a practical content representation that allows users to visualize static or dynamic scenes in a more immersive way and can be directly exploited in systems aiming to provide immersive experiences with higher degrees of freedom [4], so PC recently becomes one of the first choices to represent 3D visual contents and has a wider variety of applications with the development of VR/AR [5], [6].…”