Deploying Autonomous Underwater Vehicles (AUVs) is a necessity to enable a range of civilian/military underwater applications; yet, achieving a reliable coordination among the vehicles is a challenging issue due to the time- and space-varying characteristics of the acoustic communication channel. The design of a Medium Access Control (MAC) based on a probabilistic Space Division Multiple Access (SDMA) method for short/medium distances (less than $2\; \mathrm {km}$2 km ) is presented. This method considers the inherent vehicle position uncertainty due to the inaccuracies in models and the drift of the vehicles. It minimizes the acoustic interference statistically by considering the angular position of neighboring vehicles via a two-step estimation and by keeping the transmitter antenna's beamwidth of each vehicle at an optimal value. Such value is chosen considering three contrasting goals, i.e.: $(i)$(i) spreading the signal beam towards the vehicle to combat position uncertainty using a coarse estimation; $(ii)$(ii) focusing the beam to reduce acoustic energy dispersion through a fine estimation; and $(iii)$(iii) minimizing interference to other vehicles. Simulation results in a sparse underwater network show that this approach mitigates interference, reduces the probability of retransmission, and achieves higher data rates over conventional underwater MAC techniques.

中文翻译：

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水下声学稀疏网络中的概率空间分割多路访问

部署自主水下航行器 (AUV) 是实现一系列民用/军用水下应用的必要条件；然而，由于声学通信通道的时空变化特性，在车辆之间实现可靠的协调是一个具有挑战性的问题。基于概率空分多址 (SDMA) 方法的媒体访问控制 (MAC) 设计用于短/中距离（小于$2\; \mathrm {公里}$2 公里 ） 被表达。该方法考虑了由于模型不准确和车辆漂移而导致的固有车辆位置不确定性。它通过两步估计考虑相邻车辆的角位置并将每个车辆的发射器天线的波束宽度保持在最佳值，从而在统计上最小化声学干扰。选择这样的值时考虑了三个不同的目标，即：$(i)$(一世) 使用粗略估计向车辆传播信号束以对抗位置不确定性； $(ii)$(一世一世)通过精细估计聚焦波束以减少声能分散；和$(iii)$(一世一世一世)尽量减少对其他车辆的干扰。稀疏水下网络中的仿真结果表明，与传统的水下 MAC 技术相比，这种方法减轻了干扰，降低了重传的可能性，并实现了更高的数据速率。