{"title":"A simple ray-sector signal strength model for indoor 802.11 networks","authors":"Xiaoyan Li, R. Martin","doi":"10.1109/MAHSS.2005.1542854","DOIUrl":null,"url":null,"abstract":"In this paper we present a simple ray-sector model of signal strength for indoor 802.11 networks. Signal strength is an important parameter for a variety of important wireless networking tasks, such as localization and topology control. A sufficiently accurate, yet generic, method of generating signal strength maps is needed in order to accurately simulate, design and evaluate these systems. Our ray-sector model constructs signal maps by adding signal bias with sectors defined by rings and randomized rays, using a traditional log-linear decay model as a baseline. We show our model generates distortions similar to measured radio maps by quantitatively comparing the behavior of micro-benchmarks using maps from two buildings and those generated by our model. Finally, we demonstrate the utility of our model for higher-level applications by showing it accurately predicts the performance for two dissimilar localization algorithms","PeriodicalId":268267,"journal":{"name":"IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MAHSS.2005.1542854","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper we present a simple ray-sector model of signal strength for indoor 802.11 networks. Signal strength is an important parameter for a variety of important wireless networking tasks, such as localization and topology control. A sufficiently accurate, yet generic, method of generating signal strength maps is needed in order to accurately simulate, design and evaluate these systems. Our ray-sector model constructs signal maps by adding signal bias with sectors defined by rings and randomized rays, using a traditional log-linear decay model as a baseline. We show our model generates distortions similar to measured radio maps by quantitatively comparing the behavior of micro-benchmarks using maps from two buildings and those generated by our model. Finally, we demonstrate the utility of our model for higher-level applications by showing it accurately predicts the performance for two dissimilar localization algorithms