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A Holistic Approach of Achieving Accurate Radio Location Estimation in Long Range Wide Area Network

A Holistic Approach of Achieving Accurate Radio Location Estimation in Long Range Wide Area Network

Udora Nwabuoku Nwawelu, Mamilus Aginwa Ahaneku
Copyright: © 2022 |Volume: 14 |Issue: 1 |Pages: 14
ISSN: 1941-8663|EISSN: 1941-8671|EISBN13: 9781683180937|DOI: 10.4018/IJITN.312256
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MLA

Nwawelu, Udora Nwabuoku, and Mamilus Aginwa Ahaneku. "A Holistic Approach of Achieving Accurate Radio Location Estimation in Long Range Wide Area Network." IJITN vol.14, no.1 2022: pp.1-14. http://doi.org/10.4018/IJITN.312256

APA

Nwawelu, U. N. & Ahaneku, M. A. (2022). A Holistic Approach of Achieving Accurate Radio Location Estimation in Long Range Wide Area Network. International Journal of Interdisciplinary Telecommunications and Networking (IJITN), 14(1), 1-14. http://doi.org/10.4018/IJITN.312256

Chicago

Nwawelu, Udora Nwabuoku, and Mamilus Aginwa Ahaneku. "A Holistic Approach of Achieving Accurate Radio Location Estimation in Long Range Wide Area Network," International Journal of Interdisciplinary Telecommunications and Networking (IJITN) 14, no.1: 1-14. http://doi.org/10.4018/IJITN.312256

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Abstract

Position accuracy at any point in time has been a thing of great concern around the globe. Solution has been provided through radio devices with location estimation capabilities. Results have shown that the available location estimation algorithm has recorded improvement in terms of location accuracy and reliability. However, improving location accuracy should be a continuous process as security of life, and properties ought to be given a high priority. For this reason, currently, many localization algorithms are available. This work investigated two localization algorithms that were formulated based on the principle of multiple linear regression, namely weighted multiple linear regression (WMLR) and improved weighted multiple linear regression (iWMLR) algorithms, in order to suggest a better terminal localization algorithm. Location accuracy, range of errors, and R2 scores are the basis on which the aforementioned algorithms are evaluated. Finally, localization algorithm with high location estimation accuracy is proposed.

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