{"title":"基于结构干扰的无线传感器网络快速细粒度计数和识别","authors":"Dingming Wu, Chao Dong, Shaojie Tang, Haipeng Dai, Guihai Chen","doi":"10.1109/IPSN.2014.6846752","DOIUrl":null,"url":null,"abstract":"Counting and identifying neighboring active nodes are two fundamental operations in wireless sensor networks (WSNs). In this paper, we propose two mechanisms, Power based Counting (Poc) and Power based Identification (Poid), which achieve fast and accurate counting and identification by allowing neighbors to respond simultaneously to a poller. A key observation that motivates our design is that the power of a superposed signal increases with the number of component signals under the condition of constructive interference (CI). However, due to the phase offsets and various hardware limitations (e.g., ADC saturation), the increased superposed power exhibits dynamic and diminishing returns as the number of component signals increases. This uncertainty of phase offsets and diminishing returns property of the superposed power pose serious challenges to the design of both Poc and Poid. To overcome these challenges, we design delay compensation methods to reduce the phase offset of each component signal, and propose a novel probabilistic estimation technique in cooperation with CI. We implement Poc and Poid on a testbed of 1 USRP and 50 TelosB nodes, the experimental results show that the accuracy of Poc is above 97.9%, and the accuracy of Poid is above 96.5% for most cases. In addition to their high accuracy, our methods demonstrate significant advantages over the state-of-the-art solutions in terms of substantially lower energy consumption and estimation delay.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Fast and fine-grained counting and identification via constructive interference in WSNs\",\"authors\":\"Dingming Wu, Chao Dong, Shaojie Tang, Haipeng Dai, Guihai Chen\",\"doi\":\"10.1109/IPSN.2014.6846752\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Counting and identifying neighboring active nodes are two fundamental operations in wireless sensor networks (WSNs). In this paper, we propose two mechanisms, Power based Counting (Poc) and Power based Identification (Poid), which achieve fast and accurate counting and identification by allowing neighbors to respond simultaneously to a poller. A key observation that motivates our design is that the power of a superposed signal increases with the number of component signals under the condition of constructive interference (CI). However, due to the phase offsets and various hardware limitations (e.g., ADC saturation), the increased superposed power exhibits dynamic and diminishing returns as the number of component signals increases. This uncertainty of phase offsets and diminishing returns property of the superposed power pose serious challenges to the design of both Poc and Poid. To overcome these challenges, we design delay compensation methods to reduce the phase offset of each component signal, and propose a novel probabilistic estimation technique in cooperation with CI. We implement Poc and Poid on a testbed of 1 USRP and 50 TelosB nodes, the experimental results show that the accuracy of Poc is above 97.9%, and the accuracy of Poid is above 96.5% for most cases. In addition to their high accuracy, our methods demonstrate significant advantages over the state-of-the-art solutions in terms of substantially lower energy consumption and estimation delay.\",\"PeriodicalId\":297218,\"journal\":{\"name\":\"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPSN.2014.6846752\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPSN.2014.6846752","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast and fine-grained counting and identification via constructive interference in WSNs
Counting and identifying neighboring active nodes are two fundamental operations in wireless sensor networks (WSNs). In this paper, we propose two mechanisms, Power based Counting (Poc) and Power based Identification (Poid), which achieve fast and accurate counting and identification by allowing neighbors to respond simultaneously to a poller. A key observation that motivates our design is that the power of a superposed signal increases with the number of component signals under the condition of constructive interference (CI). However, due to the phase offsets and various hardware limitations (e.g., ADC saturation), the increased superposed power exhibits dynamic and diminishing returns as the number of component signals increases. This uncertainty of phase offsets and diminishing returns property of the superposed power pose serious challenges to the design of both Poc and Poid. To overcome these challenges, we design delay compensation methods to reduce the phase offset of each component signal, and propose a novel probabilistic estimation technique in cooperation with CI. We implement Poc and Poid on a testbed of 1 USRP and 50 TelosB nodes, the experimental results show that the accuracy of Poc is above 97.9%, and the accuracy of Poid is above 96.5% for most cases. In addition to their high accuracy, our methods demonstrate significant advantages over the state-of-the-art solutions in terms of substantially lower energy consumption and estimation delay.