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

L. Ezema, C. Ani
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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.
GSM网络中移动位置估计的加权多元线性回归模型
犯罪和事故的数量,以及其他具有挑战性的问题,要求具有本地化功能的移动应用程序正在增加。然而,移动电话提供的位置信息还没有得到充分利用。在蜂窝网络上实现移动位置定位的精度和成本一直是研究的热点问题。本文采用加权多元线性回归(WMLR)方法对移动站(MS)位置定位进行统计建模。所提出的统计建模方法是基于接收信号强度(RSS)技术。该模型提高了定位精度。利用尼日利亚埃努古一个轻城市环境中GSM网络的实测数据,对模型的模拟结果进行了分析,并与现有的MLR进行了比较。
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