Ordinary least squares in COST 231 Hata key parameters optimization base on experimental data

V. Drozdova, R. Akhpashev
{"title":"Ordinary least squares in COST 231 Hata key parameters optimization base on experimental data","authors":"V. Drozdova, R. Akhpashev","doi":"10.1109/SIBIRCON.2017.8109878","DOIUrl":null,"url":null,"abstract":"In this paper authors designed an application to increase the coverage path loss prediction. Nowadays there are a lot of the empirical and semi-empirical of radio propagation models. The models show the behavior of the radio signal spreading through the space. In this article, the COST 231 Hata model was considered. The model was made for the specific geographical location and electromagnetic conditions of the Earth. The main problem of the model is by using it in different places with different electromagnetic conditions and geographical locations. Because of these conditions, the model is not applied for different places. Authors was developed an application to increase the accuracy of path-loss prediction. The mobile application based on Android was developed to get information about signal strength and GSP location. To increase the accuracy authors used the linear regression method called Ordinary Least Squares.","PeriodicalId":135870,"journal":{"name":"2017 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIBIRCON.2017.8109878","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

In this paper authors designed an application to increase the coverage path loss prediction. Nowadays there are a lot of the empirical and semi-empirical of radio propagation models. The models show the behavior of the radio signal spreading through the space. In this article, the COST 231 Hata model was considered. The model was made for the specific geographical location and electromagnetic conditions of the Earth. The main problem of the model is by using it in different places with different electromagnetic conditions and geographical locations. Because of these conditions, the model is not applied for different places. Authors was developed an application to increase the accuracy of path-loss prediction. The mobile application based on Android was developed to get information about signal strength and GSP location. To increase the accuracy authors used the linear regression method called Ordinary Least Squares.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于实验数据的COST 231 Hata关键参数的普通最小二乘优化
本文设计了一个提高覆盖路径损失预测的应用程序。目前有许多经验和半经验的无线电传播模型。这些模型显示了无线电信号在空间中传播的行为。在本文中,考虑了COST 231 Hata模型。该模型是针对地球的特定地理位置和电磁条件而建立的。该模型的主要问题是在电磁条件和地理位置不同的地方使用。由于这些条件,该模型并不适用于不同的地方。作者开发了一个应用程序,以提高路径损失预测的准确性。开发了基于Android的移动应用程序,用于获取信号强度和GSP位置信息。为了提高准确性,作者使用了称为普通最小二乘的线性回归方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Bipolar transistor application for «on-line» neutron fluence registration Efficiency analysis of the image impulse noise cleaning using median filters with weighted central element Q-hypernets as a new model of dynamical multi-layer networks Modeling the risk of osteopenia and osteoporosis in postmenopausal women with type 2 diabetes on the sets of clinical and immunogenetic parameters Energy-efficient monitoring of the strip by identical one side directed devices
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1