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Weighted Multiple Linear Regression Model for Mobile Location Estimation in GSM Network

Weighted Multiple Linear Regression Model for Mobile Location Estimation in GSM Network

Longinus Sunday Ezema, Cosmas I. Ani
Copyright: © 2020 |Volume: 12 |Issue: 1 |Pages: 13
ISSN: 1941-8663|EISSN: 1941-8671|EISBN13: 9781799806011|DOI: 10.4018/IJITN.2020010105
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MLA

Longinus Sunday Ezema, and Cosmas I. Ani. "Weighted Multiple Linear Regression Model for Mobile Location Estimation in GSM Network." IJITN vol.12, no.1 2020: pp.57-69. http://doi.org/10.4018/IJITN.2020010105

APA

Longinus Sunday Ezema & Ani, C. I. (2020). Weighted Multiple Linear Regression Model for Mobile Location Estimation in GSM Network. International Journal of Interdisciplinary Telecommunications and Networking (IJITN), 12(1), 57-69. http://doi.org/10.4018/IJITN.2020010105

Chicago

Longinus Sunday Ezema, and Cosmas I. Ani. "Weighted Multiple Linear Regression Model for Mobile Location Estimation in GSM Network," International Journal of Interdisciplinary Telecommunications and Networking (IJITN) 12, no.1: 57-69. http://doi.org/10.4018/IJITN.2020010105

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Abstract

The numbers of crimes and accidents, among other challenging issues, requiring a mobile application with localization capabilities are on the increase. Yet there is under-utilization of location information provided by mobile phones. The accuracy and cost of implementation of mobile position localization on cellular network have been an issue of research interest. In this paper, the statistical modelling of mobile station (MS) position location was carried out using weighted multiple linear regressions (WMLR) method. The proposed statistical modelling approach was based on received signal strength (RSS) technique. The model improved localization accuracy. The model's simulated results were analysed and compared with the existing MLR using real measured data collected from GSM network in a light urban environment in Enugu, Nigeria.