Popescu, AM, Salman, N and Kemp, AH (2015) Rician statistical assumptions for geographic routing in wireless sensor networks. IET Wireless Sensor Systems, 5 (4). pp. 204-209. ISSN 2043-6386
Abstract
Geographic routing algorithms for wireless sensor networks need to be resilient to the inherent location errors of positioning systems. Proposed forwarding algorithms in the literature make use of the statistical assumption of Gaussian distributed location error and Ricianly distributed distance estimates between sensor nodes. In this study, the validity of the Rician hypothesis when realistic localisation is employed and simulated is analysed. The authors consider received signal strength-based localisation through the linear least square method. Anchor nodes estimate the position of the target sensor nodes as well as their error characteristics, which are no longer assumed Gaussian. Both theoretical and simulation results confirm that the Rician assumption is not true when realistic localisation scenarios are used, affecting the performance of geographic routing algorithms based on this statistical supposition.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) The Institution of Engineering and Technology, 2015. This paper is a postprint of a paper submitted to and accepted for publication in IET Wireless Sensor Systems and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 May 2016 15:05 |
Last Modified: | 16 Nov 2016 08:23 |
Published Version: | http://dx.doi.org/10.1049/iet-wss.2014.0023 |
Status: | Published |
Publisher: | Institution of Engineering and Technology (IET) |
Identification Number: | 10.1049/iet-wss.2014.0023 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:92870 |