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用于超声水下通信的窄带信道的测量与建模

Measurement and Modeling of Narrowband Channels for Ultrasonic Underwater Communications.

作者信息

Cañete Francisco J, López-Fernández Jesús, García-Corrales Celia, Sánchez Antonio, Robles Encarnación, Rodrigo Francisco J, Paris José F

机构信息

Departamento de Ingeniería de Comunicaciones, ETS Ingeniería de Telecomunicación, Universidad de Málaga, Málaga 29071, Spain.

Sociedad Anónima de Electrónica Submarina (SAES), Cartagena 30205, Spain.

出版信息

Sensors (Basel). 2016 Feb 19;16(2):256. doi: 10.3390/s16020256.

DOI:10.3390/s16020256
PMID:26907281
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4801632/
Abstract

Underwater acoustic sensor networks are a promising technology that allow real-time data collection in seas and oceans for a wide variety of applications. Smaller size and weight sensors can be achieved with working frequencies shifted from audio to the ultrasonic band. At these frequencies, the fading phenomena has a significant presence in the channel behavior, and the design of a reliable communication link between the network sensors will require a precise characterization of it. Fading in underwater channels has been previously measured and modeled in the audio band. However, there have been few attempts to study it at ultrasonic frequencies. In this paper, a campaign of measurements of ultrasonic underwater acoustic channels in Mediterranean shallow waters conducted by the authors is presented. These measurements are used to determine the parameters of the so-called κ-μ shadowed distribution, a fading model with a direct connection to the underlying physical mechanisms. The model is then used to evaluate the capacity of the measured channels with a closed-form expression.

摘要

水下声学传感器网络是一项很有前景的技术,可用于在海洋中进行实时数据采集,以满足各种应用需求。通过将工作频率从音频频段转移到超声波频段,可以实现尺寸更小、重量更轻的传感器。在这些频率下,衰落现象在信道特性中显著存在,网络传感器之间可靠通信链路的设计需要对其进行精确表征。水下信道中的衰落此前已在音频频段进行过测量和建模。然而,在超声波频率下对其进行研究的尝试很少。本文介绍了作者在地中海浅水区进行的一系列超声波水下声学信道测量。这些测量用于确定所谓的κ-μ阴影分布的参数,这是一种与潜在物理机制直接相关的衰落模型。然后使用该模型通过闭式表达式评估测量信道的容量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/af9976ad90ec/sensors-16-00256-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/8b81759c4c6b/sensors-16-00256-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/75fa74e02d3b/sensors-16-00256-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/68197ecccb47/sensors-16-00256-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/0bd147bbf15d/sensors-16-00256-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/90738af0e2ea/sensors-16-00256-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/8f33640ce4df/sensors-16-00256-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/af9976ad90ec/sensors-16-00256-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/8b81759c4c6b/sensors-16-00256-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/75fa74e02d3b/sensors-16-00256-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/68197ecccb47/sensors-16-00256-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/0bd147bbf15d/sensors-16-00256-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/90738af0e2ea/sensors-16-00256-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/8f33640ce4df/sensors-16-00256-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/232b/4801632/af9976ad90ec/sensors-16-00256-g007.jpg

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