Suppr超能文献

基于协作通信的水下无线传感器网络协议综述

Cooperative Communication Based Protocols for Underwater Wireless Sensors Networks: A Review.

作者信息

Khan Muhammad Shoaib, Petroni Andrea, Biagi Mauro

机构信息

Department of Information, Electronics and Telecommunications (DIET) Engineering, Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy.

Fondazione Ugo Bordoni (FUB), Viale America 201, 00144 Rome, Italy.

出版信息

Sensors (Basel). 2024 Jun 29;24(13):4248. doi: 10.3390/s24134248.

Abstract

Underwater wireless sensor networks are gaining popularity since supporting a broad range of applications, both military and civilian. Wireless acoustics is the most widespread technology adopted in underwater networks, the realization of which must face several challenges induced by channel propagation like signal attenuation, multipath and latency. In order to address such issues, the attention of researchers has recently focused on the concept of cooperative communication and networking, borrowed from terrestrial systems and to be conveniently recast in the underwater scenario. In this paper, we present a comprehensive literature review about cooperative underwater wireless sensor networks, investigating how nodes cooperation can be exploited at the different levels of the network protocol stack. Specifically, we review the diversity techniques employable at the physical layer, error and medium access control link layer protocols, and routing strategies defined at the network layer. We also provide numerical results and performance comparisons among the most widespread approaches. Finally, we present the current and future trends in cooperative underwater networks, considering the use of machine learning algorithms to efficiently manage the different aspects of nodes cooperation.

摘要

水下无线传感器网络正日益受到欢迎,因为它支持广泛的军事和民用应用。无线声学是水下网络中采用最广泛的技术,其实现必须面对由信道传播引起的几个挑战,如信号衰减、多径和延迟。为了解决这些问题,研究人员最近将注意力集中在从陆地系统借鉴并在水下场景中适当重塑的协作通信和网络概念上。在本文中,我们对协作式水下无线传感器网络进行了全面的文献综述,研究如何在网络协议栈的不同层次利用节点协作。具体来说,我们回顾了可用于物理层的分集技术、错误和介质访问控制链路层协议,以及在网络层定义的路由策略。我们还提供了最广泛使用的方法之间的数值结果和性能比较。最后,考虑到使用机器学习算法来有效管理节点协作的不同方面,我们介绍了协作式水下网络的当前和未来趋势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ea9/11244465/9f66e31d86cb/sensors-24-04248-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验