Since autonomous underwater vehicles (AUVs) are increasing popular in maritime applications, underwater wireless communication with multiple users is becoming more important and practical. In this paper, we investigate the resource allocation in underwater acoustic networks (UAN) with time division multiple access (TDMA) technique. When the uncertain channel state information (CSI) derived from the movement of AUVs in underwater environment is considered, probability constraints are introduced to guarantee the quality of service (QoS). A joint optimization algorithm is proposed, in order to schedule time for energy harvesting (EH) and wireless information transfer (WIT); the proposed algorithm also allocates transmit power to multiple AUVs to maximize the sum-throughput over a time period. The constraints of outage probability and available energy are both considered. The probability constraint is first transformed into an equivalent formulation. Furthermore, an approach with low computational complexity is proposed for power allocation and time assignment based on the residual energy of the buoy. In extensive simulation experiments, the proposed algorithm shows significant throughput increases in long term compared to baseline schemes, and better performance in terms of convergence and energy efficiency (EE) can be achieved.

由于自主水下航行器（AUV）在海上应用中越来越受欢迎，因此与多个用户的水下无线通信变得越来越重要和实用。在本文中，我们使用时分多址（TDMA）技术研究水下声学网络（UAN）中的资源分配。当考虑水下环境中AUV的运动所产生的不确定信道状态信息（CSI）时，引入了概率约束以保证服务质量（QoS）。为了调度能量收集（EH）和无线信息传输（WIT）的时间，提出了一种联合优化算法。所提出的算法还为多个AUV分配了发射功率，以在一定时间内最大化总吞吐量。都考虑了中断概率和可用能量的约束。首先将概率约束转换为等效公式。此外，基于浮标的剩余能量，提出了一种用于计算功率分配和时间分配的计算复杂度低的方法。在广泛的仿真实验中，与基线方案相比，所提出的算法在长期内显示出显着的吞吐量增加，并且在收敛性和能效（EE）方面可以实现更好的性能。