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基于SVC视频流的低复杂度多播组分解算法

杨静璇 徐桢

杨静璇, 徐桢. 基于SVC视频流的低复杂度多播组分解算法[J]. 北京航空航天大学学报, 2022, 48(7): 1278-1286. doi: 10.13700/j.bh.1001-5965.2021.0014
引用本文: 杨静璇, 徐桢. 基于SVC视频流的低复杂度多播组分解算法[J]. 北京航空航天大学学报, 2022, 48(7): 1278-1286. doi: 10.13700/j.bh.1001-5965.2021.0014
YANG Jingxuan, XU Zhen. Low computational-cost multicast subgrouping for SVC streams[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(7): 1278-1286. doi: 10.13700/j.bh.1001-5965.2021.0014(in Chinese)
Citation: YANG Jingxuan, XU Zhen. Low computational-cost multicast subgrouping for SVC streams[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(7): 1278-1286. doi: 10.13700/j.bh.1001-5965.2021.0014(in Chinese)

基于SVC视频流的低复杂度多播组分解算法

doi: 10.13700/j.bh.1001-5965.2021.0014
基金项目: 

国家自然科学基金 91638301

国家自然科学基金 91738301

详细信息
    通讯作者:

    徐桢, E-mail: xuzhen@buaa.edu.cn

  • 中图分类号: TN92;TN919.8

Low computational-cost multicast subgrouping for SVC streams

Funds: 

National Natural Science Foundation of China 91638301

National Natural Science Foundation of China 91738301

More Information
  • 摘要:

    多播是一种高效率利用带宽资源的技术,可以有效缓解多媒体传输过程中的带宽压力,但传统的多播技术会带来“瓶颈用户”问题,限制多播组内用户的数据速率。多播组分解技术将多播组划分为若干子组并以不同速率接收数据,可以有效解决瓶颈用户带来的速率限制。构建了面向用户端的视频多播传输方案,将可伸缩视频编码(SVC)的分层特点和组分解技术相结合,各多播子组根据实际接收能力解调得到不同质量的SVC视频数据,在保证用户基本视频数据传输的基础上,实现总系统速率最大化。提出了面向资源公平调配的低复杂度多播组分解算法,在改进低复杂度分组(LCS)算法过程中考虑SVC视频层限制,并引入常值向量抑制资源分配不公的情况。经过实验数据模拟和性能评估,所提算法在带宽资源和用户数量变化时,均可以稳定地保持较高的系统速率、频谱效率及系统公平性,且计算复杂度较低,能够实际应用于4G和5G网络架构下的视频传输。

     

  • 图 1  系统模型

    Figure 1.  System model

    图 2  视频层传输模型

    Figure 2.  Video layer transmission model

    图 3  信道带宽不变时的系统速率比较

    Figure 3.  System rate comparison with constant channel bandwidth

    图 4  信道带宽不变时的系统公平性比较

    Figure 4.  System fairness comparison with constant channel bandwidth

    图 5  信道带宽不变时的频谱效率比较

    Figure 5.  Spectral efficiency comparison with constant channel bandwidth

    图 6  信道带宽可变时的系统速率比较

    Figure 6.  System rate comparison with variable channel bandwidth

    图 7  信道带宽可变时的系统公平性比较

    Figure 7.  System fairness comparison with variable channel bandwidth

    图 8  信道带宽可变时的频谱效率比较

    Figure 8.  Spectral efficiency comparison with variable channel bandwidth

    图 9  不同视频流的系统速率比较

    Figure 9.  System rate comparison of different video streams

    图 10  不同视频流的系统公平性比较

    Figure 10.  System fairness comparison of different video streams

    图 11  不同视频流的频谱效率比较

    Figure 11.  Spectral efficiency comparison of different video streams

    表  1  CQI-MCS映射表[14]

    Table  1.   CQI-MCS Mapping[14]

    CQI编号 调制方式 码率*1 024 效率
    1 QPSK 78 0.152 3
    2 QPSK 120 0.234 4
    3 QPSK 193 0.377
    4 QPSK 308 0.601 6
    5 QPSK 449 0.877
    6 QPSK 602 1.175 8
    7 16QAM 378 1.476 6
    8 16QAM 490 1.914 1
    9 16QAM 616 2.406 3
    10 64QAM 466 2.730 5
    11 64QAM 567 3.322 3
    12 64QAM 666 3.902 3
    13 64QAM 772 4.523 4
    14 64QAM 873 5.115 2
    15 64QAM 948 5.554 7
    下载: 导出CSV

    表  2  主要仿真参数

    Table  2.   Main simulation assumptions

    参数 数值
    每个RB的带宽/kHz 180
    小区半径/km 2
    可用MCS等级 15
    噪声功率密度/(dBm·Hz-1) -174
    路径损耗/dB 128.1+37.6lg d
    穿透损耗/dB 20
    基站发射功率/dBm 28
    注: d为无线信号传播距离。
    下载: 导出CSV

    表  3  视频流源速率

    Table  3.   Source rates of video stream

    视频流 源速率/(Mbit·s-1)
    BL EL1 EL2 EL3
    CREW 0.306 0.578 0.814 1.184
    FOREMAN 0.170 0.407 0.589 0.890
    BUS 0.185 0.390 0.567 0.857
    ICE 0.277 0.548 0.767 1.123
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-01-11
  • 录用日期:  2021-03-26
  • 刊出日期:  2021-04-09

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