• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

不同水环境下水下无线传感器网络的射频路径与吸收损耗估计

RF Path and Absorption Loss Estimation for Underwater Wireless Sensor Networks in Different Water Environments.

作者信息

Qureshi Umair Mujtaba, Shaikh Faisal Karim, Aziz Zuneera, Shah Syed M Zafi S, Sheikh Adil A, Felemban Emad, Qaisar Saad Bin

机构信息

Department of Computer Science, City University of Hong Kong, Kowloon, 852, Hong Kong, China.

Department of Telecommunication, Mehran University of Engineering and Technology, Jamshoro 76062, Pakistan.

出版信息

Sensors (Basel). 2016 Jun 16;16(6):890. doi: 10.3390/s16060890.

DOI:10.3390/s16060890
PMID:27322263
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4934316/
Abstract

Underwater Wireless Sensor Network (UWSN) communication at high frequencies is extremely challenging. The intricacies presented by the underwater environment are far more compared to the terrestrial environment. The prime reason for such intricacies are the physical characteristics of the underwater environment that have a big impact on electromagnetic (EM) signals. Acoustics signals are by far the most preferred choice for underwater wireless communication. Because high frequency signals have the luxury of large bandwidth (BW) at shorter distances, high frequency EM signals cannot penetrate and propagate deep in underwater environments. The EM properties of water tend to resist their propagation and cause severe attenuation. Accordingly, there are two questions that need to be addressed for underwater environment, first what happens when high frequency EM signals operating at 2.4 GHz are used for communication, and second which factors affect the most to high frequency EM signals. To answer these questions, we present real-time experiments conducted at 2.4 GHz in terrestrial and underwater (fresh water) environments. The obtained results helped in studying the physical characteristics (i.e., EM properties, propagation and absorption loss) of underwater environments. It is observed that high frequency EM signals can propagate in fresh water at a shallow depth only and can be considered for a specific class of applications such as water sports. Furthermore, path loss, velocity of propagation, absorption loss and the rate of signal loss in different underwater environments are also calculated and presented in order to understand why EM signals cannot propagate in sea water and oceanic water environments. An optimal solk6ution for underwater communication in terms of coverage distance, bandwidth and nature of communication is presented, along with possible underwater applications of UWSNs at 2.4 GHz.

摘要

高频水下无线传感器网络(UWSN)通信极具挑战性。与陆地环境相比,水下环境带来的复杂情况要多得多。造成这种复杂情况的主要原因是水下环境的物理特性对电磁(EM)信号有很大影响。到目前为止,声学信号是水下无线通信最优先的选择。由于高频信号在较短距离内具有大带宽(BW)的优势,高频电磁信号无法在水下环境中深入穿透和传播。水的电磁特性往往会阻碍它们的传播并导致严重衰减。因此,针对水下环境有两个问题需要解决,一是当使用工作在2.4 GHz的高频电磁信号进行通信时会发生什么,二是哪些因素对高频电磁信号影响最大。为了回答这些问题,我们展示了在陆地和水下(淡水)环境中于2.4 GHz进行的实时实验。获得的结果有助于研究水下环境的物理特性(即电磁特性、传播和吸收损耗)。可以观察到高频电磁信号仅能在淡水的浅深度传播,并且可考虑用于特定类型的应用,如水上游乐运动。此外,还计算并展示了不同水下环境中的路径损耗、传播速度、吸收损耗和信号损耗率,以便理解为什么电磁信号不能在海水和大洋水环境中传播。提出了一种在覆盖距离、带宽和通信性质方面针对水下通信的最优解决方案,以及2.4 GHz的UWSN可能的水下应用。

相似文献

1
RF Path and Absorption Loss Estimation for Underwater Wireless Sensor Networks in Different Water Environments.不同水环境下水下无线传感器网络的射频路径与吸收损耗估计
Sensors (Basel). 2016 Jun 16;16(6):890. doi: 10.3390/s16060890.
2
Underwater Communications for Video Surveillance Systems at 2.4 GHz.2.4GHz视频监控系统的水下通信
Sensors (Basel). 2016 Oct 23;16(10):1769. doi: 10.3390/s16101769.
3
Self-Organized Proactive Routing Protocol for Non-Uniformly Deployed Underwater Networks.自组织主动式路由协议在非均匀部署水下网络中的应用。
Sensors (Basel). 2019 Dec 12;19(24):5487. doi: 10.3390/s19245487.
4
Underwater Electromagnetic Sensor Networks-Part I: Link Characterization.水下电磁传感器网络——第一部分:链路特性分析
Sensors (Basel). 2017 Jan 19;17(1):189. doi: 10.3390/s17010189.
5
Underwater wireless sensor communications in the 2.4 GHz ISM frequency band.水下 2.4GHz ISM 频段的无线传感器通信。
Sensors (Basel). 2012;12(4):4237-64. doi: 10.3390/s120404237. Epub 2012 Mar 28.
6
A Comprehensive Study on the Internet of Underwater Things: Applications, Challenges, and Channel Models.水下物联网综合研究:应用、挑战与信道模型
Sensors (Basel). 2017 Jun 22;17(7):1477. doi: 10.3390/s17071477.
7
Energy Harvesting Hybrid Acoustic-Optical Underwater Wireless Sensor Networks Localization.能量收集混合声光水下无线传感器网络定位
Sensors (Basel). 2017 Dec 26;18(1):51. doi: 10.3390/s18010051.
8
An Efficient Data-Gathering Routing Protocol for Underwater Wireless Sensor Networks.一种用于水下无线传感器网络的高效数据收集路由协议。
Sensors (Basel). 2015 Nov 17;15(11):29149-81. doi: 10.3390/s151129149.
9
Energy-Efficient Data Transmission for Underwater Wireless Sensor Networks: A Novel Hierarchical Underwater Wireless Sensor Transmission Framework.高效能水下无线传感器网络的数据传输:一种新颖的分层水下无线传感器传输框架。
Sensors (Basel). 2023 Jun 20;23(12):5759. doi: 10.3390/s23125759.
10
A Survey on Underwater Wireless Sensor Networks: Requirements, Taxonomy, Recent Advances, and Open Research Challenges.水下无线传感器网络调查:需求、分类、最新进展和开放研究挑战。
Sensors (Basel). 2020 Sep 21;20(18):5393. doi: 10.3390/s20185393.

引用本文的文献

1
Modeling and simulation of optical wireless communication channels in IoUT considering water types turbulence and transmitter selection.考虑水类型湍流和发射机选择的物联网中光无线通信信道的建模与仿真
Sci Rep. 2025 Aug 4;15(1):28381. doi: 10.1038/s41598-025-10935-w.
2
Low power, non-intrusive 3D localization for underwater mobile robots.用于水下移动机器人的低功耗、非侵入式三维定位
Commun Eng. 2025 May 23;4(1):93. doi: 10.1038/s44172-025-00422-5.
3
Wi-Fi signal for soil moisture sensing.用于土壤湿度传感的Wi-Fi信号。

本文引用的文献

1
Underwater wireless sensor communications in the 2.4 GHz ISM frequency band.水下 2.4GHz ISM 频段的无线传感器通信。
Sensors (Basel). 2012;12(4):4237-64. doi: 10.3390/s120404237. Epub 2012 Mar 28.
Environ Monit Assess. 2024 Dec 27;197(1):109. doi: 10.1007/s10661-024-13587-x.
4
Electromagnetic field produced by radiation source submerged in non-homogeneous seawater.浸没在非均匀海水中的辐射源产生的电磁场。
Sci Rep. 2024 Sep 27;14(1):22075. doi: 10.1038/s41598-024-72036-4.
5
Advancing high-performance visible light communication with long-wavelength InGaN-based micro-LEDs.利用基于长波长氮化铟镓的微型发光二极管推进高性能可见光通信。
Sci Rep. 2024 Mar 25;14(1):7018. doi: 10.1038/s41598-024-57132-9.
6
Recent Advances in Micro-LEDs Having Yellow-Green to Red Emission Wavelengths for Visible Light Communications.用于可见光通信的发射波长为黄绿到红光的微型发光二极管的最新进展
Micromachines (Basel). 2023 Feb 18;14(2):478. doi: 10.3390/mi14020478.
7
Kinematic Loggers-Development of Rugged Sensors and Recovery Systems for Field Measurements of Stone Rolling Dynamics and Impact Accelerations during Floods.运动记录仪-坚固传感器的开发和回收系统,用于洪水期间对滚石动力学和冲击加速度进行现场测量。
Sensors (Basel). 2022 Jan 28;22(3):1013. doi: 10.3390/s22031013.
8
A Robust UWSN Handover Prediction System Using Ensemble Learning.基于集成学习的稳健 UWCS 切换预测系统。
Sensors (Basel). 2021 Aug 27;21(17):5777. doi: 10.3390/s21175777.
9
Inductive Tracking Methodology for Wireless Sensors in Photoreactors.光反应器中无线传感器的感应跟踪方法。
Sensors (Basel). 2021 Jun 18;21(12):4201. doi: 10.3390/s21124201.
10
Multi-Sensor Fusion for Underwater Vehicle Localization by Augmentation of RBF Neural Network and Error-State Kalman Filter.基于径向基函数神经网络增强与误差状态卡尔曼滤波器的水下航行器多传感器融合定位方法
Sensors (Basel). 2021 Feb 6;21(4):1149. doi: 10.3390/s21041149.