{"title":"基于隐马尔可夫模型的移动网络信道分类","authors":"Rafiaa Boujbel","doi":"10.30958/ajte.2-1-3","DOIUrl":null,"url":null,"abstract":"In telecommunication networks, Key Performance Indicators (KPIs) are monitored to ensure higher Quality of Service (QoS) in communication networks. With the significant increase of data traffic on the mobile network, a detailed analysis of the transmission quality is becoming increasingly important. Existing classification approaches are widely considered to classify network traffic and not the channel in itself. The aim of this work is to implement a channel estimation tool based on hidden Markov models that is able to determine transmission channel characteristics in mobile radio receivers.","PeriodicalId":434189,"journal":{"name":"GI-Jahrestagung","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Channel classification with hidden Markov models in mobile networks\",\"authors\":\"Rafiaa Boujbel\",\"doi\":\"10.30958/ajte.2-1-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In telecommunication networks, Key Performance Indicators (KPIs) are monitored to ensure higher Quality of Service (QoS) in communication networks. With the significant increase of data traffic on the mobile network, a detailed analysis of the transmission quality is becoming increasingly important. Existing classification approaches are widely considered to classify network traffic and not the channel in itself. The aim of this work is to implement a channel estimation tool based on hidden Markov models that is able to determine transmission channel characteristics in mobile radio receivers.\",\"PeriodicalId\":434189,\"journal\":{\"name\":\"GI-Jahrestagung\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-02-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"GI-Jahrestagung\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30958/ajte.2-1-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"GI-Jahrestagung","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30958/ajte.2-1-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Channel classification with hidden Markov models in mobile networks
In telecommunication networks, Key Performance Indicators (KPIs) are monitored to ensure higher Quality of Service (QoS) in communication networks. With the significant increase of data traffic on the mobile network, a detailed analysis of the transmission quality is becoming increasingly important. Existing classification approaches are widely considered to classify network traffic and not the channel in itself. The aim of this work is to implement a channel estimation tool based on hidden Markov models that is able to determine transmission channel characteristics in mobile radio receivers.