{"title":"快速衰落信道上TDS-OFDM系统的卡尔曼均衡","authors":"Guoqiang Gong, Wan-Cheng Ge","doi":"10.1109/KAMW.2008.4810460","DOIUrl":null,"url":null,"abstract":"By analyzing the characteristic of fast fading channels, a Kalman equalization method of directly estimating channel values in time domain is proposed based on time domain synchronization orthogonal frequency division multiplexing (TDS-OFDM) system models. The proposed algorithm is one-dimensional Kalman method and has low complexity. In addition, for tracking the time-varying channel, a minimum mean-squared error (MMSE) equalizer in time domain and a iterative decision-feedback method are also proposed. For given signal-to-noise ratios (SNRs), the simulation results show that the proposed algorithm has better performance than the other algorithms in fast fading channels.","PeriodicalId":375613,"journal":{"name":"2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Kalman Equalization for TDS-OFDM Systems over Fast Fading Channels\",\"authors\":\"Guoqiang Gong, Wan-Cheng Ge\",\"doi\":\"10.1109/KAMW.2008.4810460\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"By analyzing the characteristic of fast fading channels, a Kalman equalization method of directly estimating channel values in time domain is proposed based on time domain synchronization orthogonal frequency division multiplexing (TDS-OFDM) system models. The proposed algorithm is one-dimensional Kalman method and has low complexity. In addition, for tracking the time-varying channel, a minimum mean-squared error (MMSE) equalizer in time domain and a iterative decision-feedback method are also proposed. For given signal-to-noise ratios (SNRs), the simulation results show that the proposed algorithm has better performance than the other algorithms in fast fading channels.\",\"PeriodicalId\":375613,\"journal\":{\"name\":\"2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KAMW.2008.4810460\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KAMW.2008.4810460","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Kalman Equalization for TDS-OFDM Systems over Fast Fading Channels
By analyzing the characteristic of fast fading channels, a Kalman equalization method of directly estimating channel values in time domain is proposed based on time domain synchronization orthogonal frequency division multiplexing (TDS-OFDM) system models. The proposed algorithm is one-dimensional Kalman method and has low complexity. In addition, for tracking the time-varying channel, a minimum mean-squared error (MMSE) equalizer in time domain and a iterative decision-feedback method are also proposed. For given signal-to-noise ratios (SNRs), the simulation results show that the proposed algorithm has better performance than the other algorithms in fast fading channels.