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QpE-aware video streaming for SVC over multiuser MIMO-OFDM systems

机译:通过多用户MIMO-OFDM系统实现SVC的QpE感知视频流

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摘要

We propose a QpE-aware video streaming solution to maximize multiuser QoE for Scalable Video Coding (SVC) streaming over multiuser (MU) Multiple-Input Multiple-Output (MIMO)-Orthogonal Frequency Division Multiplexing (OFDM) systems. We achieve it by integrating novel QpE-aware video adaptation (QoEVA) and QoE-aware resource allocation (QoERA) schemes. We first study QoEVA of SVC via a subjective video quality assessment database and derive QoE-optimized scalability adaptation tracks. A rate-QoE model is then constructed to approximate the track and is employed to design QoERA. By proving the NP-hardness of the QoERA problem, we propose an adaptive solution where resource block assignment, power allocation and modulation selection are jointly optimized to enhance multiuser QoE. Experimental results show that the proposed QoEVA significantly performs better than the conventional video adaptation schemes and the proposed QoERA achieves much better user experience when compared to state-of-the-art solutions. Our solution can be employed for both pre-coded and live video streaming.
机译:我们提出了一种QpE感知视频流解决方案,以在多用户(MU)多输入多输出(MIMO)-正交频分复用(OFDM)系统上最大化可伸缩视频编码(SVC)流的多用户QoE。我们通过集成新颖的QpE感知视频自适应(QoEVA)和QoE感知资源分配(QoERA)方案来实现这一目标。我们首先通过主观视频质量评估数据库研究SVC的QoEVA,并得出QoE优化的可伸缩性适应轨道。然后构建一个速率QoE模型以近似轨道,并用于设计QoERA。通过证明QoERA问题的NP硬度,我们提出了一种自适应解决方案,其中资源块分配,功率分配和调制选择被共同优化以增强多用户QoE。实验结果表明,与最新的解决方案相比,拟议的QoEVA的性能明显优于传统的视频自适应方案,并且拟议的QoERA获得了更好的用户体验。我们的解决方案可用于预编码和实时视频流。

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