Optimizing the Number and Size of Signature Cells in a Modulated Sensor System

A. Olteanu
{"title":"Optimizing the Number and Size of Signature Cells in a Modulated Sensor System","authors":"A. Olteanu","doi":"10.1145/3585967.3585970","DOIUrl":null,"url":null,"abstract":"The localization and tracking capabilities of binary sensors can be significantly enhanced by associating sensor nodes with modulators. The addition of modulators segments the detection area into subregions, called signature cells. While much of the related research focuses on modulator design and sensor data processing, there are few studies on the optimum number of cells, especially when considering small area cells with small area variances. This paper studies the optimum number of cells for varying numbers of per-sensor modulators under a placement scenario that produces signature cells with small area variances. We first derive the optimum number of signature cells and find necessary and sufficient conditions under which the maximum is achieved. We then focus on the sensors’ spatial awareness and deduct the conditions under which maximal spatial awareness is achieved. Finally, we study the asymptotic behavior of the individual cells’ areas in terms of the number of modulators. Our study can guide researchers in enhancing the tracking and localization precision of applications and improve the spatial awareness of sensors.","PeriodicalId":275067,"journal":{"name":"Proceedings of the 2023 10th International Conference on Wireless Communication and Sensor Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2023 10th International Conference on Wireless Communication and Sensor Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3585967.3585970","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The localization and tracking capabilities of binary sensors can be significantly enhanced by associating sensor nodes with modulators. The addition of modulators segments the detection area into subregions, called signature cells. While much of the related research focuses on modulator design and sensor data processing, there are few studies on the optimum number of cells, especially when considering small area cells with small area variances. This paper studies the optimum number of cells for varying numbers of per-sensor modulators under a placement scenario that produces signature cells with small area variances. We first derive the optimum number of signature cells and find necessary and sufficient conditions under which the maximum is achieved. We then focus on the sensors’ spatial awareness and deduct the conditions under which maximal spatial awareness is achieved. Finally, we study the asymptotic behavior of the individual cells’ areas in terms of the number of modulators. Our study can guide researchers in enhancing the tracking and localization precision of applications and improve the spatial awareness of sensors.
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
调制传感器系统中特征单元数量和大小的优化
通过将传感器节点与调制器相关联,可以显著提高二元传感器的定位和跟踪能力。调制器的加入将检测区域分割成子区域,称为特征细胞。虽然许多相关研究集中在调制器设计和传感器数据处理上,但很少有关于最佳细胞数的研究,特别是在考虑小面积细胞和小面积方差的情况下。本文研究了在产生具有小面积差异的特征单元的放置场景下,不同数量的每传感器调制器的最佳单元数。我们首先推导了签名单元的最优数量,并找到了达到最大值的充分必要条件。然后,我们重点研究了传感器的空间感知,并推导了实现最大空间感知的条件。最后,我们根据调制器的数量研究了单个细胞面积的渐近行为。本研究可以指导研究人员提高应用的跟踪和定位精度,提高传感器的空间感知能力。
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
Design of border security system based on ultrasonic technology and video linkage A research of convolutional neural network model deployment in low- to medium-performance microcontrollers An SISO-OTFS Channel Parameter Learning Scheme in Time-Frequency Domain Research on Sampling Estimation Method for Complex Networks-Oriented Network Autonomous Learning Monitoring System Based on SVM Algorithm
×
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:604180095
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