{"title":"工业无线共存环境的统计分析与预测建模","authors":"G. Shrestha, Kaleem Ahmad, U. Meier","doi":"10.1109/WFCS.2012.6242554","DOIUrl":null,"url":null,"abstract":"Typically, cognitive radio systems either sense the channel just before transmission or perform this task periodically in order to remain aware about the operational environment. However, a channel sensed as `free' can become busy during the transmission of the cognitive system resulting in harmful collisions and unnecessary interruptions in the secondary user data transmission. As a solution, predictive based approaches has been proposed and has shown promising results in simulated environments. However, modeling real-time, dynamic, coexisting environments demand investigation with real-time demonstrators. This paper investigates industrial coexisting environments and illustrates the prediction model selection and its parameter estimation criteria. Based on the investigation a real-time testbed is implemented using a CC2500 TRX and MSP430 μC based platform.","PeriodicalId":110610,"journal":{"name":"2012 9th IEEE International Workshop on Factory Communication Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Statistical analysis and predictive modeling of industrial wireless coexisting environments\",\"authors\":\"G. Shrestha, Kaleem Ahmad, U. Meier\",\"doi\":\"10.1109/WFCS.2012.6242554\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Typically, cognitive radio systems either sense the channel just before transmission or perform this task periodically in order to remain aware about the operational environment. However, a channel sensed as `free' can become busy during the transmission of the cognitive system resulting in harmful collisions and unnecessary interruptions in the secondary user data transmission. As a solution, predictive based approaches has been proposed and has shown promising results in simulated environments. However, modeling real-time, dynamic, coexisting environments demand investigation with real-time demonstrators. This paper investigates industrial coexisting environments and illustrates the prediction model selection and its parameter estimation criteria. Based on the investigation a real-time testbed is implemented using a CC2500 TRX and MSP430 μC based platform.\",\"PeriodicalId\":110610,\"journal\":{\"name\":\"2012 9th IEEE International Workshop on Factory Communication Systems\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 9th IEEE International Workshop on Factory Communication Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WFCS.2012.6242554\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 9th IEEE International Workshop on Factory Communication Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WFCS.2012.6242554","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical analysis and predictive modeling of industrial wireless coexisting environments
Typically, cognitive radio systems either sense the channel just before transmission or perform this task periodically in order to remain aware about the operational environment. However, a channel sensed as `free' can become busy during the transmission of the cognitive system resulting in harmful collisions and unnecessary interruptions in the secondary user data transmission. As a solution, predictive based approaches has been proposed and has shown promising results in simulated environments. However, modeling real-time, dynamic, coexisting environments demand investigation with real-time demonstrators. This paper investigates industrial coexisting environments and illustrates the prediction model selection and its parameter estimation criteria. Based on the investigation a real-time testbed is implemented using a CC2500 TRX and MSP430 μC based platform.