Streaming 360-degree VR Video with Statistical QoS Provisioning in mmWave Networks from Delay and Rate Perspectives

TL;DR

This paper introduces a novel VR streaming architecture for mmWave networks that optimizes resource use and guarantees statistical QoS by combining joint unicast/multicast task assignment, stochastic QoS modeling, and adaptive transmission strategies.

Contribution

It proposes an innovative VR streaming framework addressing overlapping FoVs, statistical QoS provisioning, and loss-tolerant data discarding, with new algorithms for resource-efficient task assignment and adaptive transmission.

Findings

The proposed task assignment scheme conserves wireless resources effectively.

The SQP framework accurately models delay and rate QoS requirements.

The adaptive transmission scheme outperforms baseline methods in resource utilization and QoS guarantees.

Abstract

Millimeter-wave(mmWave) technology has emerged as a promising enabler for unleashing the full potential of 360-degree virtual reality (VR). However, the explosive growth of VR services, coupled with the reliability issues of mmWave communications, poses enormous challenges in terms of wireless resource and quality-of-service (QoS) provisioning for mmWave-enabled 360-degree VR. In this paper, we propose an innovative 360-degree VR streaming architecture that addresses three under-exploited issues: overlapping field-of-views (FoVs), statistical QoS provisioning (SQP), and loss-tolerant active data discarding. Specifically, an overlapping FoV-based optimal joint unicast and multicast (JUM) task assignment scheme is designed to implement the non-redundant task assignments, thereby conserving wireless resources remarkably. Furthermore, leveraging stochastic network calculus, we develop a comprehensive SQP theoretical framework that encompasses two SQP schemes from delay and rate perspectives. Additionally, a corresponding optimal adaptive joint time-slot allocation and active-discarding (ADAPT-JTAAT) transmission scheme is proposed to minimize resource consumption while guaranteeing diverse statistical QoS requirements under loss-intolerant and loss-tolerant scenarios from delay and rate perspectives, respectively. Extensive simulations demonstrate the effectiveness of the designed overlapping FoV-based JUM optimal task assignment scheme. Comparisons with six baseline schemes validate that the proposed optimal ADAPTJTAAT transmission scheme can achieve superior SQP performance in resource utilization, flexible rate control, and robust queue behaviors.