Energy-Efficient VR 360 Video Streaming in the IRS-Aided Rate-Splitting Multiple Access Network
Long Teng, Qingqing Wu, Huiyu Duan, Xiongkuo Min, Guangtao Zhai · IEEE Transactions on Communications · 2025
Maximizing energy efficiency in VR 360 video transmission is essential for advancing VR applications. Motivated by this goal, we conduct a comprehensive study that integrates the characteristics of VR 360 video with beamforming strategies and intelligent reflecting surface (IRS) shifting techniques in the rate-splitting multiple access (RSMA) network. In the IRS-aided RSMA network, we propose a stable energy-efficient transmission (SEET) scheme aimed at minimizing the number of transmitted VR video chunks. The SEET scheme constructs a stable pre-transmission and playback flow, ensuring seamless and continuous display of the upcoming content without latency. We also propose a mixed-format-based chunk (MFC) method that simultaneously pre-transmits both 2D and 3D chunk frames to each user, further enhancing energy efficiency. We utilize an alternating optimization method to divide the original energy-efficient problem into three subproblems. To tackle the non-convex and NP-hard beamforming subproblem, we utilize the first-order Taylor expansion and then obtain the approximate transmission rates of common messages and private messages regarding the quadratic form of beamforming vectors. We then utilize quadratically constrained programming, fractional programming, and linear programming to obtain the near-optimal solutions for beamforming vectors, IRS phase shifts, and RSMA parameters, respectively. The final numerical results affirm that the proposed SEET scheme can notably minimize the beamforming power of the base station. Through the SEET scheme, the MFC method with the approximation method exhibits superior energy efficiency, outperforming existing transmission methods in terms of both energy utility and consumption by HMDs.