QoE-Oriented Resource Allocation for 360-degree Video Transmission over Heterogeneous Networks

TL;DR

This paper proposes a resource allocation scheme for 360-degree video streaming over heterogeneous networks, optimizing user experience by jointly exploiting LTE and Wi-Fi bandwidth, utilizing video saliency, user view prediction, and buffer strategies.

Contribution

It introduces a novel application-layer scheme that combines bandwidth exploitation, user view prediction, and buffer management for improved QoE in 360-degree video streaming.

Findings

The scheme achieves higher QoE in simulations.

It effectively balances resource utilization across LTE and Wi-Fi.

The buffer strategy reduces the impact of prediction errors.

Abstract

Immersive media streaming, especially virtual reality (VR)/360-degree video streaming which is very bandwidth demanding, has become more and more popular due to the rapid growth of the multimedia and networking deployments. To better explore the usage of resource and achieve better quality of experience (QoE) perceived by users, this paper develops an application-layer scheme to jointly exploit the available bandwidth from the LTE and Wi-Fi networks in 360-degree video streaming. This newly proposed scheme and the corresponding solution algorithms utilize the saliency of video, prediction of users' view and the status information of users to obtain an optimal association of the users with different Wi-Fi access points (APs) for maximizing the system's utility. Besides, a novel buffer strategy is proposed to mitigate the influence of short-time prediction problem for transmitting 360-degree videos in time-varying networks. The promising performance and low complexity of the proposed scheme and algorithms are validated in simulations with various 360-degree videos.