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基于云端软件定义水声的跨域通信系统

姚可星 官权升 谢佳轩 赵昊 王焱

姚可星, 官权升, 谢佳轩, 等. 基于云端软件定义水声的跨域通信系统[J]. 水下无人系统学报, 2024, 32(4): 688-694 doi: 10.11993/j.issn.2096-3920.2024-0075
引用本文: 姚可星, 官权升, 谢佳轩, 等. 基于云端软件定义水声的跨域通信系统[J]. 水下无人系统学报, 2024, 32(4): 688-694 doi: 10.11993/j.issn.2096-3920.2024-0075
YAO Kexing, GUAN Quansheng, XIE Jiaxuan, ZHAO Hao, WANG Yan. Cross-Domain Communication System with Cloud-Based Software-Defined Acoustic[J]. Journal of Unmanned Undersea Systems, 2024, 32(4): 688-694. doi: 10.11993/j.issn.2096-3920.2024-0075
Citation: YAO Kexing, GUAN Quansheng, XIE Jiaxuan, ZHAO Hao, WANG Yan. Cross-Domain Communication System with Cloud-Based Software-Defined Acoustic[J]. Journal of Unmanned Undersea Systems, 2024, 32(4): 688-694. doi: 10.11993/j.issn.2096-3920.2024-0075

基于云端软件定义水声的跨域通信系统

doi: 10.11993/j.issn.2096-3920.2024-0075
基金项目: 国家自然科学基金(U23A20281); 广东省科技计划项目资助(2023A0505050097).
详细信息
    作者简介:

    姚可星(1995-), 男, 在读博士, 主要研究方向为水声通信、声电协同等

  • 中图分类号: TJ6; U675.7

Cross-Domain Communication System with Cloud-Based Software-Defined Acoustic

  • 摘要: 由于水声通信性能的制约, 跨水-空界面的数据传输性能难以进一步提升。针对该问题, 文中提出了一种基于云端软件定义水声(C-SDA)的跨域通信系统架构。C-SDA将水声接收机从水面中继节点移动到云端(即监测中心), 并利用无线电通信带宽交换云端计算资源进行水声信号解调和解码。中继网关的水声-无线电双栈网络协议被简化为单栈结构, 避免了数据包的封装和再封装, 节省了硬件成本。C-SDA不仅能实现先进的通信信号处理, 而且能促进水声通信技术的更新和迭代。现场测试实验结果表明, 与自研的嵌入式水声接收机相比, C-SDA能够适用更高性能的均衡器, 使误码率得到显著改善。

     

  • 图  1  C-SDA 系统模型

    Figure  1.  Model of the C-SDA system

    图  2  C-SDA系统框架设计

    Figure  2.  Architecture design of the C-SDA system

    图  3  C-SDA方案与传统方案跨域通信协议体系对比

    Figure  3.  Comparison of cross-domain communication protocol architecture between C-SDA scheme and traditional scheme

    图  4  整体实验场景

    Figure  4.  Scenario of the overall experiment

    图  5  不同复杂度下Turbo均衡算法性能比较

    Figure  5.  Performance comparison of Turbo equalization algorithms with different complexities

    图  6  嵌入式水声通信机

    Figure  6.  Embedded underwater acoustic communication machine

    图  7  嵌入式系统与PC系统相同算法处理效率对比

    Figure  7.  Comparison of processing efficiency of the same algorithm between embedded system and PC system

    图  8  云端接收机BER随中继采样率变化曲线

    Figure  8.  Curves of BER of the cloud receiver with relay sampling rate

    表  1  不同均衡器算法复杂度

    Table  1.   Algorithm complexity of different equalizers

    均衡算法 复杂度
    MAP $ O\left( {{q^{M - 1}}} \right) $
    MMSE $ O\left( {{M^2} + {N^2}} \right) $
    app-MMSE $ O\left( {M + N} \right) $
    下载: 导出CSV
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    [9] ZHILIN I V, BUSHNAQ O M, MASI G D, et al. A universal multimode(acoustic, magnetic induction, optical, RF) software defined modem architecture for underwater communication[J]. IEEE Transactions on Wireless Communications, 2023, 22(12): 9105-9116. doi: 10.1109/TWC.2023.3268418
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出版历程
  • 收稿日期:  2024-05-01
  • 修回日期:  2024-06-03
  • 录用日期:  2024-06-13
  • 网络出版日期:  2024-06-24

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