Multi-system-multi-operator localization in PLMN using neural networks

M. Borenovic; A. Neskovic; D. Budimir

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Multi-system-multi-operator localization in PLMN using neural networks

机译：使用神经网络的PLMN中的多系统多操作员定位

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Providing the localization algorithm for context-aware services is the focus of many studies. This paper explores the properties of positioning models based on received signal strength (RSS) in PLMN (Public Land Mobile Network) networks. The effects of using the RSS at a mobile terminal from various systems, such as GSM and UMTS, as well as from multiple operators, have been investigated and discussed. Twenty-two models, based on artificial neural networks, have been developed and verified using the data from an immense measurement campaign. The obtained results show that augmenting the model with additional RSS data, even from systems with poor radio-visibility, may improve the positioning accuracy to as much as a 35 m median distance error in a light urban environment. The degradation of accuracy in indoor environments and the complexity and latency of the models were also scrutinized.

机译：提供用于上下文感知服务的本地化算法是许多研究的重点。本文探讨了基于PLMN（公共陆地移动网络）网络中的接收信号强度（RSS）的定位模型的特性。已经研究和讨论了在各种系统（例如GSM和UMTS）以及多个运营商的移动终端上使用RSS的效果。已经开发了22个基于人工神经网络的模型，并使用来自大量测量活动的数据进行了验证。获得的结果表明，即使在无线电可见性较差的系统中，使用附加的RSS数据来扩展模型，也可以在轻型城市环境中将定位精度提高到35 m的中值距离误差。还研究了室内环境精度的下降以及模型的复杂性和延迟。

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来源
《International journal of communication systems》 |2012年第2期|p.67-83|共17页
作者
M. Borenovic; A. Neskovic; D. Budimir;
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作者单位

Wireless Communications Research Group, School of Electronics and Computer Science,University of Westminster, London W1W 6UW, U.K;

Radio Research Lab, School of Electrical Engineering, University of Belgrade, Belgrade, Serbia;

Wireless Communications Research Group, School of Electronics and Computer Science,University of Westminster, London W1W 6UW, U.K;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
land mobile radio cellular systems; localization; neural networks; positioning; received signal strength;

机译：陆地移动无线电蜂窝系统;本土化;神经网络;定位;接收信号强度;

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Multi-system-multi-operator localization in PLMN using neural networks

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