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；然而，基于人机动态交互的新型水下监测应用和系统需要实时多媒体采集和分类。遥控车辆（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与支撑船相连，或者必须定期上升到水面，通过射频（RF）波与远程站通信，这限制了任务的执行。无线水声通信是典型的水下通信物理层技术；然而，由于声波具有衰减、带宽有限、多普勒扩频、传播延迟大、误码率高、信道时变等特点，使得视频传输难以实现。由于这些原因，最先进的声学通信解决方案仍然主要集中在实现延迟容忍、低带宽/低数据速率的标量数据传输，或者至多几十Kbps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，以实现数百千比特/秒（Kbps）的鲁棒，可靠和高数据速率的水下多媒体流；(2)研究在集成基于微机电（MEMS）的声矢量传感器（avs）的创新软件定义测试平台架构上集成多种环境中可用的通信方法的问题，该架构将使处理密集型物理层功能作为软件定义，但在硬件中执行，可由用户根据体验质量（QoE）实时重新配置。在任务1中，将利用多天线阵列和avs，提出一种新的物理层解决方案，以提高水声传输的数据速率，从而在水下传输高分辨率视频。采用一种新颖的概率方法，设计一种有效的介质访问控制（MAC）层解决方案，利用自动驾驶系统可靠地共享被操纵车辆之间的空间，从而减少声干扰。采用基于avs估计到达角度的鲁棒闭环混合自动重传请求（ARQ）编码技术，可以提高多媒体传输的质量。在任务2中，将对SEANet G2声学网络平台进行修改，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，将使用导航器、avs和SEANet测试平台定义场景来验证任务1中提出的想法；任务2将通过将SEANet集成到浮标和导航员以及avs中来评估，以建立一个进行视频传输实验的测试平台。任务1和任务2还将通过比较MEMs自动驾驶系统与商用现货（COTS）自动驾驶系统的优缺点，以及评估半自主的人机环功能来提高用户QoE。该奖项反映了美国国家科学基金会的法定使命，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，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.