Simulators are essential to troubleshoot and optimize Underwater Acoustic Network (UAN) schemes (network protocols and communication technologies) before real field experiments. However, due to programming differences between the above two contents, most existing simulators concentrate on one while weakening the other, leading to non-generic simulations and biased performance results. Moreover, novel UAN schemes increasingly integrate Artificial Intelligence (AI) techniques, yet existing simulators lack support for necessary AI frameworks, failing to train and evaluate these intelligent methods. On the other hand, these novel schemes consider more UAN characteristics involving more complex parameter configurations, which also challenges simulators in flexibility and fineness. To keep abreast of advances in UANs, we propose the Fourth Generation (FG) ns-3-based simulator Aqua-Sim~FG, enhancing the general and intelligent simulation ability. On the basis of retaining previous generations' functions, we design a new general architecture, which is compatible with various programming languages, including MATLAB, C++, and Python. In this way, Aqua-Sim~FG provides a general environment to simulate communication technologies, network protocols, and AI models simultaneously. In addition, we expand six new features from node and communication levels by considering the latest UAN methods' requirements, which enhances the simulation flexibility and fineness of Aqua-Sim~FG. Experimental results show that Aqua-Sim~FG can simulate UANs' performance realistically, reflect intelligent methods' problems in real-ocean scenarios, and provide more effective troubleshooting and optimization for actual UANs. The basic simulator is available at https://github.com/JLU-smartocean/aqua-sim-fg.

翻译：仿真器对于在水声网络实际现场实验前进行网络方案（包括网络协议与通信技术）的故障排查与性能优化至关重要。然而，由于上述两方面内容在编程实现上存在差异，现有大多数仿真器往往侧重其一而弱化另一，导致仿真缺乏通用性且性能结果存在偏差。此外，新兴的水声网络方案日益融合人工智能技术，但现有仿真器缺乏对必要AI框架的支持，无法训练和评估这些智能方法。另一方面，这些新方案考虑了更多水声网络特性，涉及更复杂的参数配置，也对仿真器的灵活性与精细度提出了挑战。为紧跟水声网络领域的发展，我们提出了基于ns-3的第四代仿真器Aqua-Sim~FG，以增强通用与智能仿真能力。在保留前代功能的基础上，我们设计了一种新的通用架构，该架构兼容多种编程语言，包括MATLAB、C++和Python。通过这种方式，Aqua-Sim~FG能够为通信技术、网络协议和AI模型提供同步仿真的通用环境。此外，我们结合最新水声网络方法的需求，从节点与通信层面扩展了六项新特性，从而提升了Aqua-Sim~FG的仿真灵活性与精细度。实验结果表明，Aqua-Sim~FG能够真实模拟水声网络的性能，反映智能方法在真实海洋场景中存在的问题，并为实际水声网络提供更有效的故障排查与优化支持。基础仿真器可在https://github.com/JLU-smartocean/aqua-sim-fg获取。