Bandwidth-Constrained MAP Estimation for Wireless Sensor Networks

S.F.A. Shah, A. Ribeiro, G. Giannakis
{"title":"Bandwidth-Constrained MAP Estimation for Wireless Sensor Networks","authors":"S.F.A. Shah, A. Ribeiro, G. Giannakis","doi":"10.1109/ACSSC.2005.1599735","DOIUrl":null,"url":null,"abstract":"We deal with distributed parameter estimation algorithms for use in wireless sensor networks (WSNs) with a fusion center when only quantized observations are available due to power/bandwidth constraints. The main goal of the paper is to design efficient estimators when the parameter can be modelled as random with a priori information. In particular, we develop maximum a posteriori (MAP) estimators for distributed parameter estimation and formulate the problem under different scenarios. We show that the pertinent objective function is concave and hence, the corresponding MAP estimator can be obtained efficiently through simple numerical maximization algorithms","PeriodicalId":326489,"journal":{"name":"Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2005-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.2005.1599735","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23

Abstract

We deal with distributed parameter estimation algorithms for use in wireless sensor networks (WSNs) with a fusion center when only quantized observations are available due to power/bandwidth constraints. The main goal of the paper is to design efficient estimators when the parameter can be modelled as random with a priori information. In particular, we develop maximum a posteriori (MAP) estimators for distributed parameter estimation and formulate the problem under different scenarios. We show that the pertinent objective function is concave and hence, the corresponding MAP estimator can be obtained efficiently through simple numerical maximization algorithms
基于带宽约束的无线传感器网络MAP估计
我们处理了分布式参数估计算法,用于具有融合中心的无线传感器网络(WSNs),当由于功率/带宽限制只有量化观测可用时。本文的主要目标是设计有效的估计器,当参数可以用先验信息随机建模时。特别是,我们开发了用于分布参数估计的最大后验估计器(MAP),并在不同场景下阐述了问题。我们证明了相关的目标函数是凹的,因此,通过简单的数值最大化算法可以有效地获得相应的MAP估计量
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信