Received signal strength indication based distance measurement using lambert function for underwater wireless sensor network localization

Localization issue is a crucial part of Wireless Sensor Networks (WSNs) including Underwater WSNs (UWSNs). Unlike in Terrestrial WSNs where the localization techniques are well established, localization for UWSNs is still at the infancy stage. Most of the existing localizations proposed are based on...

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Main Author:	Hosseini, Majid
Format:	Thesis
Language:	English
Published:	2010
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/11484/6/MajidHosseiniMFSKSM2010.pdf
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spelling	my-utm-ep.114842017-09-18T06:35:41Z Received signal strength indication based distance measurement using lambert function for underwater wireless sensor network localization 2010-01 Hosseini, Majid QA75 Electronic computers. Computer science Localization issue is a crucial part of Wireless Sensor Networks (WSNs) including Underwater WSNs (UWSNs). Unlike in Terrestrial WSNs where the localization techniques are well established, localization for UWSNs is still at the infancy stage. Most of the existing localizations proposed are based on Time of Arrival (ToA) and many of them assume an ideal environment and precise synchronization among sensor nodes. This research has proposed a new localization technique for UWSN based on Received Signal Strength Indication (RSSI). Extensive study has been carried out on the application of Lambert W function for an accurate distance measurement within five iterations. The technique that utilizes Lambert W function and RSS has been developed. The technique is divided into three separate steps including initialization, distance measurement and position estimation. This new localization technique has a two-level computation approach that allows sensor nodes to have coarse estimations of their locations, while the sink, which has more resources, calculates accurate positions. The new RSS-based localization is compared to ToA-based localization using MATLAB with variety of oceanographic properties considered. The simulation results showed that the new localization technique can achieve far better accuracy in all conditions. Besides, the proposed technique is less susceptible to errors caused by the environment factors as compared to ToA-based methods. It is also power-efficient, as the main part of the localization computations is computed at the sink rather than sensor nodes. 2010-01 Thesis http://eprints.utm.my/id/eprint/11484/ http://eprints.utm.my/id/eprint/11484/6/MajidHosseiniMFSKSM2010.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information Systems Faculty of Computer Science and Information System
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Hosseini, Majid Received signal strength indication based distance measurement using lambert function for underwater wireless sensor network localization
description	Localization issue is a crucial part of Wireless Sensor Networks (WSNs) including Underwater WSNs (UWSNs). Unlike in Terrestrial WSNs where the localization techniques are well established, localization for UWSNs is still at the infancy stage. Most of the existing localizations proposed are based on Time of Arrival (ToA) and many of them assume an ideal environment and precise synchronization among sensor nodes. This research has proposed a new localization technique for UWSN based on Received Signal Strength Indication (RSSI). Extensive study has been carried out on the application of Lambert W function for an accurate distance measurement within five iterations. The technique that utilizes Lambert W function and RSS has been developed. The technique is divided into three separate steps including initialization, distance measurement and position estimation. This new localization technique has a two-level computation approach that allows sensor nodes to have coarse estimations of their locations, while the sink, which has more resources, calculates accurate positions. The new RSS-based localization is compared to ToA-based localization using MATLAB with variety of oceanographic properties considered. The simulation results showed that the new localization technique can achieve far better accuracy in all conditions. Besides, the proposed technique is less susceptible to errors caused by the environment factors as compared to ToA-based methods. It is also power-efficient, as the main part of the localization computations is computed at the sink rather than sensor nodes.
format	Thesis
qualification_level	Master's degree
author	Hosseini, Majid
author_facet	Hosseini, Majid
author_sort	Hosseini, Majid
title	Received signal strength indication based distance measurement using lambert function for underwater wireless sensor network localization
title_short	Received signal strength indication based distance measurement using lambert function for underwater wireless sensor network localization
title_full	Received signal strength indication based distance measurement using lambert function for underwater wireless sensor network localization
title_fullStr	Received signal strength indication based distance measurement using lambert function for underwater wireless sensor network localization
title_full_unstemmed	Received signal strength indication based distance measurement using lambert function for underwater wireless sensor network localization
title_sort	received signal strength indication based distance measurement using lambert function for underwater wireless sensor network localization
granting_institution	Universiti Teknologi Malaysia, Faculty of Computer Science and Information Systems
granting_department	Faculty of Computer Science and Information System
publishDate	2010
url	http://eprints.utm.my/id/eprint/11484/6/MajidHosseiniMFSKSM2010.pdf
_version_	1747814861597835264

Received signal strength indication based distance measurement using lambert function for underwater wireless sensor network localization

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