Joint Rate and Resource Allocation for Panoramic Videos over Future Network

With the popularity of panoramic video, it is urging research on the viewpoint-aware adaptive streaming methods to alleviate the resource shortage of wireless networks thus providing higher quality of experience (QoE) for the users. Therefore, in this paper, we focus on MEC-assisted 5G heterogeneous network system, and formulate a novel joint rate and resource allocation optimization problem with the aim of maximizing the overall QoE of all users, which comprehensively takes the characteristics of panoramic video in quality assessment, the delay requirements and the resource constraints into account. To solve this problem with low complexity, a heuristic algorithm based on Lagrange Relaxation and Greedy strategy is developed. The simulation results show that our algorithm can improve the overall performance of all users in the video quality, the quality fluctuation and the interruption time.