{"title":"基于隐马尔可夫模型的高速铁路MIMO-OFDM系统链路自适应","authors":"Kun-Yi Lin, Hsin-Piao Lin, Ming-Chien Tseng","doi":"10.1109/APCC.2010.5679714","DOIUrl":null,"url":null,"abstract":"A link adaptation scheme for MIMO-OFDM systems over high speed rail environment is addressed in this paper. In this study, a selection method of MIMO transmission mode and the modulation and coding scheme (MCS) according to the Rician channel K-factor from our previous work is considered. A hidden Markov model of time-varying Rician channel K-factor is constructed by using the real measured channel data on the high speed rail train. With the constructed hidden Markov model, the time correlation of Rician channel K-factor can be obtained and the time-varying K-factor value can be generated. By using the hidden Markov model, the K-factor value can be predicted to facilitate link adaptation since the K-factor may vary during feedback, especially in high mobility scenario. Simulation results show an average throughput improvement of 5Mbps.","PeriodicalId":402292,"journal":{"name":"2010 16th Asia-Pacific Conference on Communications (APCC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Link adaptation of MIMO-OFDM systems using hidden Markov model for high speed railway\",\"authors\":\"Kun-Yi Lin, Hsin-Piao Lin, Ming-Chien Tseng\",\"doi\":\"10.1109/APCC.2010.5679714\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A link adaptation scheme for MIMO-OFDM systems over high speed rail environment is addressed in this paper. In this study, a selection method of MIMO transmission mode and the modulation and coding scheme (MCS) according to the Rician channel K-factor from our previous work is considered. A hidden Markov model of time-varying Rician channel K-factor is constructed by using the real measured channel data on the high speed rail train. With the constructed hidden Markov model, the time correlation of Rician channel K-factor can be obtained and the time-varying K-factor value can be generated. By using the hidden Markov model, the K-factor value can be predicted to facilitate link adaptation since the K-factor may vary during feedback, especially in high mobility scenario. Simulation results show an average throughput improvement of 5Mbps.\",\"PeriodicalId\":402292,\"journal\":{\"name\":\"2010 16th Asia-Pacific Conference on Communications (APCC)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 16th Asia-Pacific Conference on Communications (APCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APCC.2010.5679714\",\"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 16th Asia-Pacific Conference on Communications (APCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCC.2010.5679714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Link adaptation of MIMO-OFDM systems using hidden Markov model for high speed railway
A link adaptation scheme for MIMO-OFDM systems over high speed rail environment is addressed in this paper. In this study, a selection method of MIMO transmission mode and the modulation and coding scheme (MCS) according to the Rician channel K-factor from our previous work is considered. A hidden Markov model of time-varying Rician channel K-factor is constructed by using the real measured channel data on the high speed rail train. With the constructed hidden Markov model, the time correlation of Rician channel K-factor can be obtained and the time-varying K-factor value can be generated. By using the hidden Markov model, the K-factor value can be predicted to facilitate link adaptation since the K-factor may vary during feedback, especially in high mobility scenario. Simulation results show an average throughput improvement of 5Mbps.