Joint Communication and Computational Resource Allocation for QoE-driven Point Cloud Video Streaming

Fuzzy Logic-Based Adaptive Point Cloud Video Streaming

“…For the point cloud dataset with spare distribution, we can decompose the 3D space into a hierarchical structure of cubes and encode each point as an index of the cube to which it belongs. Note that point cloud encoding requires higher computational complexity than traditional video encoding [12], [13], which distinguishes the point cloud video streaming system from the traditional video streaming system.…”

“…Point cloud video streaming has drawn increasing attention recently [10], [11], [12], [13], [14], [15]. Most of these works are based on VR/360 video streaming schemes [1], [19], i.e., a point cloud video is divided into smaller tiles, and only tiles inside the user's field of view (FoV) (denotes the part of the video the user is watching) are transmitted, and optimization can be conducted following this thread to optimize the defined objective function [10], [11].…”

“…These factors make point cloud video streaming very different from traditional video streaming [8], [9] and should be considered in transmission scheme design. This paper focuses on point cloud video streaming, which has recently become a research hotspot [10], [11], [12], [13], [14], [15] and aims to solve the inherent technical issues to provide users with higher video quality.…”

“…[11] presented a number of rate adaptation heuristics that use information on the user's position and focus, the available bandwidth, and the client's buffer status to determine the most appropriate quality representation of each object. However, these works did not consider the decoding complexity [12], [13], i.e., the computational requirement of the existing point cloud video codec for decoding exceeds the computational capability of user devices. [12], [13] confirmed this research issue, and Li et al first proposed including uncompressed tiles to reduce the computational burden of the user device and optimize the user's quality of experience (QoE) by selecting the proper quality levels under the communication and computation resource constraints [13].…”

“…However, these works did not consider the decoding complexity [12], [13], i.e., the computational requirement of the existing point cloud video codec for decoding exceeds the computational capability of user devices. [12], [13] confirmed this research issue, and Li et al first proposed including uncompressed tiles to reduce the computational burden of the user device and optimize the user's quality of experience (QoE) by selecting the proper quality levels under the communication and computation resource constraints [13]. [14] summarized the current research progress and confirmed these unsolved technical issues.…”