NeTS: Medium: Collaborative: Reliable Underwater Acoustic Video Transmission Towards Human-Robot Dynamic Interaction

在过去的十年中，水下通信已经实现了广泛的应用，但是，有新的水下监控应用和系统的基础上，人-机器人动态交互，需要实时多媒体采集和分类。遥控潜水器（ROV）是支持这种交互式应用的关键工具，因为它们可以从人类无法轻松/安全到达的地方捕获多媒体数据;然而，水下航行器通常通过光纤电缆拴在支持船上，或者必须定期上升到水面，通过射频（RF）波与远程站进行通信，这限制了使命。无线声通信是水下通信的典型物理层技术，但由于声波具有衰减、带宽受限、多普勒扩展、高时延、高误码率和时变信道等特性，使得利用声波进行视频传输变得困难。由于这些原因，现有技术的声学通信解决方案仍然主要集中于实现延迟容忍、低带宽/低数据速率标量数据传输或至多几十Kbps量级的低质量/低分辨率多媒体流。因此，本研究计划的目标是：（1）设计新颖的通信解决方案，用于鲁棒的、可靠的和高数据速率的水下多媒体流，其数量级为每秒数百千比特（Kbps）;（2）研究在一个创新的软件定义的测试平台架构上集成多种环境中可用的通信方法的问题，该架构集成了微机电（MEMS）-基于声学矢量传感器（AVS），其将实现软件定义的处理密集型物理层功能，但是在硬件中执行，该硬件可以由用户基于体验质量（QoE）在真实的时间中重新配置。通过利用多天线阵列和AVS，在任务1中，将提出一种新颖的物理层解决方案来提高用于水下声学传输的数据速率，以便在水下传输高分辨率视频。通过遵循一种新的概率方法，一个有效的媒体访问控制（MAC）层的解决方案将被设计为可靠地共享空间之间的转向车辆通过使用AVS，以减少声学干扰。通过应用基于使用AVS的估计到达角的鲁棒的闭环混合自动重传请求（ARQ）编码技术，将提高多媒体传输的质量。在任务2中，将修改SEANet G2声学网络平台，以研究基于氮化铝（AlN）压电MEMS技术的新型小型化集成AVS阵列的设计和制造。最后，在任务3中，将使用Naviator、AVS和SEANet测试平台定义场景以验证任务1中提出的想法;将通过将SEANet集成到浮标和Naviator沿着AVS来评估任务2，以构建用于进行视频传输实验的测试平台。任务1和任务2也将通过比较MEMs AVS与商用现成（COTS）AVS的优缺点以及通过评估半自主人在回路功能来增强用户QoE来整合。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估而被认为值得支持。

In the past decade underwater communications have enabled a wide range of applications; there are, however, novel underwater monitoring applications and systems based on human-robot dynamic interaction that require real-time multimedia acquisition and classification. Remotely Operated Vehicles (ROVs) are key instruments to support such interactive applications as they can capture multimedia data from places where humans cannot easily/safely go; however, underwater vehicles are often tethered to the supporting ship by a fiber cable or have to rise periodically to the surface to communicate with a remote station via Radio Frequency (RF) waves, which constrains the mission. Wireless acoustic communication is the typical physical-layer technology for underwater communication; however, video transmissions via acoustic waves are hard to accomplish as the acoustic waves suffer from attenuation, limited bandwidth, Doppler spreading, high propagation delay, high bit error rate, and time-varying channel. For these reasons, state-of-the-art acoustic communication solutions are still mostly focusing on enabling delay-tolerant, low-bandwidth/low-data-rate scalar data transmission or at best low-quality/low-resolution multimedia streaming in the order of few tens of Kbps. Hence, the objectives of this research program are: (1) To design novel communication solutions for robust, reliable, and high-data rate underwater multimedia streaming on the order of hundreds of Kilobits per second (Kbps); (2) To investigate the problem of integrating communication methods available in multiple environments on an innovative software-defined testbed architecture integrating Microelectromechanical (MEMS)-based Acoustic Vector Sensors (AVSs) that will enable processing-intensive physical-layer functionalities as software-defined, but executed in hardware that can be reconfigured in real time by the user based on the Quality of Experience (QoE).By exploiting multiple-antenna arrays and AVSs, in Task 1 a novel physical-layer solution will be proposed to boost the data rate for underwater acoustic transmission so as to transfer high-resolution video underwater. By following a novel probabilistic approach, an efficient Medium Access Control (MAC) layer solution will be designed to share reliably the space among the steered vehicles by using AVSs so as to reduce the acoustic interference. The quality of multimedia delivery will be improved by applying a robust closed-loop hybrid Automatic Repeat Request (ARQ) coding technique based on the estimated angles of arrivals using AVSs. In Task 2, the SEANet G2 acoustic networking platform will be modified to investigate the design and fabrication of a new class of miniaturized and integrated AVS arrays based on the Aluminum Nitride (AlN) piezoelectric MEMS technology. Finally, in Task 3, scenarios will be defined to validate the ideas proposed in Task 1 using the Naviator, AVSs, and SEANet testbed; Task 2 will be evaluated by integrating SEANet to a buoy and the Naviator along with AVSs to build a testbed for conducting video transmission experiments. Tasks 1 and 2 will be also integrated by comparing the pros and cons of MEMs AVSs with Commercial Off-The-Shelf (COTS) AVSs and by evaluating the semi-autonomous human-in-the-loop features to enhance user QoE.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.