ASVTuw: Adaptive Scalable Video Transmission in Underwater Acoustic Multicast Networks
ASVTuw: Adaptive Scalable Video Transmission in Underwater Acoustic Multicast Networks
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ASVTuw：水下声学组播网络中的自适应可扩展视频传输
DOI：
10.1145/3567600.3568137
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Pompili, Dario
中科院分区：
文献类型：
--
作者：
Qi, Zhuoran;Petroccia, Roberto;Pompili, Dario
可伸缩视频编码（SVC）在视频传输中得到了广泛的应用。然而，不合适的SVC结构可能会导致接收到的视频质量低于用户要求或造成资源浪费，特别是在水下时变信道中。本文提出并验证了一种用于水声组播网络视频传输的自适应跨层解决方案，即自适应可扩展视频传输（ASVTuw）。在ASVTuw中，发射机随着时间的推移收集有关信道状态和用户视频质量要求的信息，利用机器学习（ML）自适应选择SVC视频结构和传输方案。为了收集所需的声学数据，进行了海上实验。然后将收集到的数据用于MATLAB仿真来验证ASVTuw。结果表明，与现有的非跨层设计相比，使用ASVTuw避免了传输冗余SVC子流造成的资源浪费，有效满足了组播用户对视频质量的要求，具有更高的灵活性。
Scalable Video Coding (SVC) has been widely used in video transmissions. However, inappropriate SVC structures may lead to received video quality lower than user’s requirement or resource waste, especially in underwater time-varying channels. In this work, an adaptive cross-layering solution is proposed and validated for video transmissions in underwater acoustic multicast networks, namely Adaptive Scalable Video Transmission (ASVTuw). In ASVTuw, the transmitter collects over time the information about the channel states and the users’ video quality requirements to adaptively select the SVC video structures and transmission schemes, using Machine Learning (ML). At-sea experiments were conducted to collect the required acoustic data. The collected data were then used in MATLAB simulations to validate the ASVTuw. The results show that the usage of ASVTuw avoids resource wasting from transmitting redundant SVC substreams and satisfies the multicast users’ video quality requirements effectively with higher flexibility compared with the existing noncross-layering designs.
12 kHz频段水声调制解调器测距精度的实验评估
DOI：
10.23919/icins43215.2020.9133821
发表时间：
2020
期刊：
2020 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS)
影响因子：
--
作者：
A. Rodionov;S. Kulik;F. Dubrovin;P. Unru
通讯作者：
P. Unru
QoE 驱动的无缝切换下的 H.264/SVC 与 H.264/AVC 视频质量比较
DOI：
--
发表时间：
2012
期刊：
Signal processing. Image communication
影响因子：
--
作者：
I. Politis;Lampros Dounis;T. Dagiuklas
通讯作者：
T. Dagiuklas
影响因子：
6.8
作者：
Li，Mingfu;Lee，Cheng-Han
通讯作者：
Lee，Cheng-Han