Online Resource Allocation with Energy Harvesting for Underwater Wireless Networks

水下无线通信网络在环境监测、近海勘探、防灾减灾、军事侦察等方面有着广泛的应用。 这些无线网络需要提供复杂的实时数据收集，并提供延长的部署时间，如30至50年。这项研究的目标是开发永久的水下无线网络，其中高速多输入多输出（MIMO）收发器由持久的超级电容器通过从环境能源中收集能量来供电。该项目将开发实时资源分配和随机优化解决方案，以有效地分配水下能量收集无线网络中的带宽和功率资源，同时考虑到能量收集电源的独特动态和水下信道的时间变化。所提出的方法将建立一个实用的设计方法，能量收集MIMO收发器，以实现高可靠性，高数据速率，高能效，在高动态水声通信环境的存在。该项目的另一个重要目标是通过一系列教育和外展活动培训下一代研究人员，包括课程开发，研究生和本科生培训，为当地高中机器人团队提供服务，以及参加海洋机器人比赛。这些活动还将倡导负责任的工程方法，以减少海洋中的声音污染。水下无线通信通常需要大型MIMO收发器，以达到对可靠性和吞吐量的苛刻要求。因此，用于能量收集MIMO通信的资源分配变成涉及大量设计变量的预编码和带宽分配的复杂联合设计。同时，能量收集电源的动态和水下信道的时间变化在类似的时间尺度上，因此需要在线随机优化，而不是MIMO RF网络中常用的离线资源分配。为了解决这些独特的挑战，在永久水下无线网络，该项目制定了联合在线预编码器的设计和带宽分配到一个多变量随机动态规划（SDP）的问题，并提出了一种新的嵌套优化算法来解决它迭代计算复杂度低。该项目通过一种新的嵌套优化算法和一种在线资源分配方法来推进无线通信和网络技术，该算法解决了具有线性计算复杂度的多变量SDP问题，该方法在通信信道和能源上使用随机模型，而不是通常使用的确定性模型。还将建立一个硬件测试床，以验证在线资源分配算法和超级电容能源。

Underwater wireless communication networks have found a wide range of applications, such as environmental monitoring, offshore exploration, disaster prevention, and military surveillance. These wireless networks are required to provide sophisticated real-time data collection and serve for prolonged deployment time, such as 30 to 50 years. The objective of this research is to develop perpetual underwater wireless networks in which high-speed multiple-input multiple-output (MIMO) transceivers are powered up by long-lasting super-capacitors via energy harvesting from environmental energy sources. This project will develop real-time resource allocation and stochastic optimization solutions to efficiently allocate the bandwidth and power resources in underwater energy-harvesting wireless networks, taking into account the unique dynamics of energy-harvesting power sources and the time variation of the underwater channels. The proposed approach will establish a practical design approach for energy-harvesting MIMO transceivers to achieve high reliability, high data rate, and high energy efficiency, in the presence of highly dynamic underwater acoustic communication environments. Another important goal of the project is to train next-generation researchers through a set of education and outreach activities including course development, graduate and undergraduate student training, service to local high school robotics teams, and participation in marine robotics competition. These activities will also advocate responsible engineering approaches for reducing sound pollution in oceans.Underwater wireless communications often require large MIMO transceivers to achieve the demanding requirements on reliability and throughput. As such, resource allocation for energy-harvesting MIMO communication becomes a complicated joint design of precoding and bandwidth allocation that involves a large number of design variables. Meanwhile, the dynamics of energy-harvesting power sources and the time variation of the underwater channels are on a similar time scale, thus requiring online stochastic optimization instead of the offline resource allocation commonly used in MIMO RF networks. To address these unique challenges in perpetual underwater wireless networks, this project formulates the joint online precoder design and bandwidth allocation into a multi-variable stochastic dynamic programming (SDP) problem, and proposes a novel nested optimization algorithm to solve it iteratively with low computational complexity. This project contributes to advancing wireless communications and network technology by a novel nested optimization algorithm that solves the multi-variable SDP problem with linear computational complexity and an online resource allocation method that uses stochastic models on both communication channels and energy sources rather than commonly used deterministic models. A hardware test bed will also be built to verify the online resource allocation algorithms and super-capacitor energy sources.