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Underwater Electromagnetic Sensor Networks, Part II: Localization and Network Simulations

In the first part of the paper, we modeled and characterized the underwater radio channel in shallow waters. In the second part, we analyze the application requirements for an underwater wireless sensor network (U-WSN) operating in the same environment and perform detailed simulations. We consider t...

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Autores principales: Zazo, Javier, Valcarcel Macua, Sergio, Zazo, Santiago, Pérez, Marina, Pérez-Álvarez, Iván, Jiménez, Eugenio, Cardona, Laura, Brito, Joaquín Hernández, Quevedo, Eduardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5191155/
https://www.ncbi.nlm.nih.gov/pubmed/27999309
http://dx.doi.org/10.3390/s16122176
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author Zazo, Javier
Valcarcel Macua, Sergio
Zazo, Santiago
Pérez, Marina
Pérez-Álvarez, Iván
Jiménez, Eugenio
Cardona, Laura
Brito, Joaquín Hernández
Quevedo, Eduardo
author_facet Zazo, Javier
Valcarcel Macua, Sergio
Zazo, Santiago
Pérez, Marina
Pérez-Álvarez, Iván
Jiménez, Eugenio
Cardona, Laura
Brito, Joaquín Hernández
Quevedo, Eduardo
author_sort Zazo, Javier
collection PubMed
description In the first part of the paper, we modeled and characterized the underwater radio channel in shallow waters. In the second part, we analyze the application requirements for an underwater wireless sensor network (U-WSN) operating in the same environment and perform detailed simulations. We consider two localization applications, namely self-localization and navigation aid, and propose algorithms that work well under the specific constraints associated with U-WSN, namely low connectivity, low data rates and high packet loss probability. We propose an algorithm where the sensor nodes collaboratively estimate their unknown positions in the network using a low number of anchor nodes and distance measurements from the underwater channel. Once the network has been self-located, we consider a node estimating its position for underwater navigation communicating with neighboring nodes. We also propose a communication system and simulate the whole electromagnetic U-WSN in the Castalia simulator to evaluate the network performance, including propagation impairments (e.g., noise, interference), radio parameters (e.g., modulation scheme, bandwidth, transmit power), hardware limitations (e.g., clock drift, transmission buffer) and complete MAC and routing protocols. We also explain the changes that have to be done to Castalia in order to perform the simulations. In addition, we propose a parametric model of the communication channel that matches well with the results from the first part of this paper. Finally, we provide simulation results for some illustrative scenarios.
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spelling pubmed-51911552017-01-03 Underwater Electromagnetic Sensor Networks, Part II: Localization and Network Simulations Zazo, Javier Valcarcel Macua, Sergio Zazo, Santiago Pérez, Marina Pérez-Álvarez, Iván Jiménez, Eugenio Cardona, Laura Brito, Joaquín Hernández Quevedo, Eduardo Sensors (Basel) Article In the first part of the paper, we modeled and characterized the underwater radio channel in shallow waters. In the second part, we analyze the application requirements for an underwater wireless sensor network (U-WSN) operating in the same environment and perform detailed simulations. We consider two localization applications, namely self-localization and navigation aid, and propose algorithms that work well under the specific constraints associated with U-WSN, namely low connectivity, low data rates and high packet loss probability. We propose an algorithm where the sensor nodes collaboratively estimate their unknown positions in the network using a low number of anchor nodes and distance measurements from the underwater channel. Once the network has been self-located, we consider a node estimating its position for underwater navigation communicating with neighboring nodes. We also propose a communication system and simulate the whole electromagnetic U-WSN in the Castalia simulator to evaluate the network performance, including propagation impairments (e.g., noise, interference), radio parameters (e.g., modulation scheme, bandwidth, transmit power), hardware limitations (e.g., clock drift, transmission buffer) and complete MAC and routing protocols. We also explain the changes that have to be done to Castalia in order to perform the simulations. In addition, we propose a parametric model of the communication channel that matches well with the results from the first part of this paper. Finally, we provide simulation results for some illustrative scenarios. MDPI 2016-12-17 /pmc/articles/PMC5191155/ /pubmed/27999309 http://dx.doi.org/10.3390/s16122176 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zazo, Javier
Valcarcel Macua, Sergio
Zazo, Santiago
Pérez, Marina
Pérez-Álvarez, Iván
Jiménez, Eugenio
Cardona, Laura
Brito, Joaquín Hernández
Quevedo, Eduardo
Underwater Electromagnetic Sensor Networks, Part II: Localization and Network Simulations
title Underwater Electromagnetic Sensor Networks, Part II: Localization and Network Simulations
title_full Underwater Electromagnetic Sensor Networks, Part II: Localization and Network Simulations
title_fullStr Underwater Electromagnetic Sensor Networks, Part II: Localization and Network Simulations
title_full_unstemmed Underwater Electromagnetic Sensor Networks, Part II: Localization and Network Simulations
title_short Underwater Electromagnetic Sensor Networks, Part II: Localization and Network Simulations
title_sort underwater electromagnetic sensor networks, part ii: localization and network simulations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5191155/
https://www.ncbi.nlm.nih.gov/pubmed/27999309
http://dx.doi.org/10.3390/s16122176
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