Joint Power and Channel Resource Optimization in Soft Multi-View Video Delivery
Joint Power and Channel Resource Optimization in Soft Multi-View Video Delivery
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DOI：
10.1109/access.2019.2946607
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发表时间：
2019-10
期刊：
影响因子：
3.9
通讯作者：
Ticao Zhang;S. Mao
中科院分区：
文献类型：
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作者：
Ticao Zhang;S. Mao
现有的无线多视点视频（MVV）传输方案使用数字压缩来实现更好的编码效率。然而，数字方案遭受悬崖效应，这是指视频质量是无线信道质量的阶跃函数的现象。在本文中，我们首先考虑一种软MVV传输方案，其中视图间数据和纹理深度数据之间的相关性通过5维离散余弦变换（5D-DCT）来利用。线性变换的5D-DCT信号以模拟方式调制，使得当信道质量变得更好时，视频质量适度地改善。数字解决方案中繁琐的比特和速率控制被简单的功率控制所取代。第二，随着相机数量和数据深度的增加，MVV的数据大小线性增加。为了减少软MVV传输中繁重的数据流量，我们提出了有效的资源（带宽和功率）分配算法。仿真结果表明，所提出的失真-资源（DR）优化算法能够在资源约束下保证最佳的观看质量，而所提出的资源-失真（RD）优化算法能够在满足目标视频质量要求的前提下最小化资源占用.第三，研究了纹理和深度帧上的功率控制以及视点位置对合成虚拟视点质量的影响。通过仿真验证了该算法对参考视点和虚拟视点的有效性。
Existing wireless multi-view video (MVV) transmission schemes use digital compression to achieve a better coding efficiency. However, the digital schemes suffer from the cliff effect, which refers to the phenomenon that the video quality is a step function of wireless channel quality. In this paper, we first consider a soft MVV transmission scheme where the correlations between the inter-view data and texture-depth data are exploited by a 5-dimensional discrete cosine transform (5D-DCT). The linearly transformed 5D-DCT signals are modulated in an analog manner so that the video quality gracefully improves when the channel quality becomes better. The cumbersome bit and rate controls in digital solutions are replaced by simple power controls. Second, as with the increase of the number of cameras and data depths, the data size of MVV increases linearly. To reduce the heavy data traffic in soft MVV transmission, we proposed efficient resource (bandwidth and power) allocation algorithms. Simulations results demonstrate that the proposed distortion-resource (DR) optimization algorithm can ensure a best viewing quality under a resource constraint and the proposed resource-distortion (RD) optimization algorithm can minimize the resource usage for a target video quality requirement. Third, the impact of power control across texture and depth frame and the impact of view positions on synthesized virtual view quality are investigated. The efficacy of the proposed algorithm on both the reference viewpoint as well as the virtual viewpoint is verified via simulations.