A Server-Side Optimized Hybrid Multicast-Unicast Strategy for Multi-User Adaptive 360-Degree Video Streaming

Nuowen Kan, Chengming Liu, Junni Zou, Chenglin Li, Hongkai Xiong

Abstract: The head-mounted display (HMD) for 360-degree videos cannot be shared by multiple users, which significantly increases the bandwidth consumption when multiple users request the same video content simultaneously. This paper proposes a server-side hybrid multicast-unicast strategy for multi-user adaptive 360-degree video streaming, aiming to ensure the overall quality of experience (QoE) of the users in a bandwidth-constrained environment. A framework is established to realise this strategy, through which the delivery mode (multicast or unicast) and the corresponding bitrate for each tile can be jointly adapted to the dynamics of users' throughputs and field of views (FoVs). To maximize the overall QoE, a user clustering method is proposed to classify the users into several multicast clusters. Based on these clusters, we then formulate the joint delivery mode selection and rate adaptation problem as a non-linear integer programming problem which can be solved using the steepest ascent gradient algorithm. Finally, experiments are carried out to verify the performance of the proposed strategy.