Server-Side Rate Adaptation for Multi-User 360-Degree Video Streaming

Abstract

How to balance the tradeoff between the user experience and bandwidth utilization emerges a critical challenge for multi-user 360-degree video adaptive streaming. This paper studies the server-side rate adaptation strategy for multiple users which are competing for the server bandwidth capacity. A tile visibility probability model is established, by which the tiles are classified into predicted, marginal and invisible types. A fine-grained rate adaptation problem is formulated as a nonlinear integer programming (NIP) problem, which aims at maximizing the video quality and navigation smoothness for multiple users. Thereafter, a steepest ascent algorithm with feasible starting point is developed to solve the proposed NIP problem in polynomial time. Finally, simulation results verify the performance of the proposed rate adaptation strategy.