{"title":"无线传感器网络中的节能分布式检测","authors":"Xuefen Zhang, Changchuan Yin, Guangxin Yue, Huarui Wu","doi":"10.1109/ICFN.2010.24","DOIUrl":null,"url":null,"abstract":"We consider energy-efficient Distributed Detection in wireless sensor networks. It is assumed that a group of sensors observe the same quantity in independent additive observation noises with possibly different variances. Each node computes a local statistic and communicates it to a fusion center over Rayleigh fading wireless channels.At the fusion,the linear minimum mean square error(LMMSE) is used. In this paper Two types of constraints are considered: 1) transmission power constraints at the nodes, and 2) the communication channel between the nodes and the decision center. we propose a optimal distributed estimation algorithm in energy-constrained wireless sensor networks. Finally, we demonstrate the applicability of our results through numerical examples.","PeriodicalId":185491,"journal":{"name":"2010 Second International Conference on Future Networks","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Energy-efficient Distributed Detection in Wireless Sensor Networks\",\"authors\":\"Xuefen Zhang, Changchuan Yin, Guangxin Yue, Huarui Wu\",\"doi\":\"10.1109/ICFN.2010.24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider energy-efficient Distributed Detection in wireless sensor networks. It is assumed that a group of sensors observe the same quantity in independent additive observation noises with possibly different variances. Each node computes a local statistic and communicates it to a fusion center over Rayleigh fading wireless channels.At the fusion,the linear minimum mean square error(LMMSE) is used. In this paper Two types of constraints are considered: 1) transmission power constraints at the nodes, and 2) the communication channel between the nodes and the decision center. we propose a optimal distributed estimation algorithm in energy-constrained wireless sensor networks. Finally, we demonstrate the applicability of our results through numerical examples.\",\"PeriodicalId\":185491,\"journal\":{\"name\":\"2010 Second International Conference on Future Networks\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-01-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second International Conference on Future Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICFN.2010.24\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Future Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFN.2010.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Energy-efficient Distributed Detection in Wireless Sensor Networks
We consider energy-efficient Distributed Detection in wireless sensor networks. It is assumed that a group of sensors observe the same quantity in independent additive observation noises with possibly different variances. Each node computes a local statistic and communicates it to a fusion center over Rayleigh fading wireless channels.At the fusion,the linear minimum mean square error(LMMSE) is used. In this paper Two types of constraints are considered: 1) transmission power constraints at the nodes, and 2) the communication channel between the nodes and the decision center. we propose a optimal distributed estimation algorithm in energy-constrained wireless sensor networks. Finally, we demonstrate the applicability of our results through numerical examples.