Rate-Splitting for IRS-Aided Multiuser VR Streaming: An Imitation Learning-Based Approach
Huang R, Wong VW, Schober R (2023)
Publication Type: Conference contribution
Publication year: 2023
Journal
Publisher: Institute of Electrical and Electronics Engineers Inc.
Book Volume: 2023-May
Pages Range: 3222-3227
Conference Proceedings Title: IEEE International Conference on Communications
Event location: Rome, ITA
ISBN: 9781538674628
DOI: 10.1109/ICC45041.2023.10279407
Abstract
Virtual reality (VR) applications require wireless systems to provide a high transmission rate to support 360-degree video streaming to multiple users simultaneously. In this paper, we propose an intelligent reflecting surface (IRS)-aided rate-splitting (RS) VR streaming system. In the proposed system, RS exploits the shared interests of the users in VR streaming, and the IRS creates reflected channels to facilitate a high transmission rate. The IRS also mitigates the performance bottleneck caused by the requirement that all RS users have to be able to decode the common message. We formulate an optimization problem for maximization of the achievable bitrate of the streamed 360-degree video subject to the quality-of-service (QoS) constraints of the users. We propose a deep reinforcement learning (DRL)-based algorithm, in which we leverage imitation learning and the hidden convexity of the formulated problem to optimize the IRS phase shifts, RS parameters, beamforming vectors, and bitrate selection of the 360-degree video tiles. Simulations based on a real-world dataset show that the proposed IRS-aided RS VR streaming system outperforms two baseline schemes in terms of system sum-rate and average runtime.
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APA:
Huang, R., Wong, V.W., & Schober, R. (2023). Rate-Splitting for IRS-Aided Multiuser VR Streaming: An Imitation Learning-Based Approach. In Michele Zorzi, Meixia Tao, Walid Saad (Eds.), IEEE International Conference on Communications (pp. 3222-3227). Rome, ITA: Institute of Electrical and Electronics Engineers Inc..
MLA:
Huang, Rui, Vincent W.S. Wong, and Robert Schober. "Rate-Splitting for IRS-Aided Multiuser VR Streaming: An Imitation Learning-Based Approach." Proceedings of the 2023 IEEE International Conference on Communications, ICC 2023, Rome, ITA Ed. Michele Zorzi, Meixia Tao, Walid Saad, Institute of Electrical and Electronics Engineers Inc., 2023. 3222-3227.
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