FoV-Based Hierarchical Rate Splitting for Statistical QoS-Driven VR Streaming in Cell-Free Networks

Virtual reality (VR) streaming demands both high data rates and low latency, requiring advanced transmission strategies to enhance system performance in wireless networks. This paper proposes a hierarchical rate-splitting multiple access-based cell-free (HRS-CF) VR transmission strategy, which integrates field of view (FoV)-based user grouping, scalable video coding (SVC)-based message design, and message-centric base station selection. Moreover, to characterize the statistical data rate of VR services under a given delay constraint, we investigate the effective capacity (EC) of the VR video streaming under HRS-CF strategy. Furthermore, we jointly optimize the precoding matrix, rate splitting coefficients, and BS selection using the proximal policy optimization (PPO) algorithm, where a power threshold-based BS selection is introduced to reduce computational complexity. Simulation results show that the proposed HRS-CF strategy outperforms the conventional rate splitting and CF transmission schemes, achieving at least a 16% performance improvement.