The 360-degree video streaming has higher bandwidth requirements compared with
traditional video to achieve the same user-perceived playback quality. Since users only view
part of the entire videos, viewport-adaptive streaming is an effective approach to guarantee
video quality. However, the performance of viewport-adaptive schemes is highly dependent
on the bandwidth estimation and viewport prediction. To overcome these issues, we
propose a novel reinforcement learning (RL) based viewport-adaptive streaming framework …

Tile-based rate adaption can improve the quality of experience (QoE) for adaptive 360-
degree video streaming under constrained network conditions, which, however, is a
challenging problem due to the requirements of accurate prediction for users' viewports and
optimal bitrate allocation for tiles. In this paper, we propose a strategy that deploys
reinforcement learning-based Rate Adaptation with adaptive Prediction and Tiling for 360-
degree video streaming, named RAPT360, to address these challenges. Specifically, to …