{"title":"基于栅格的带叠加导频异步IDMA信道估计","authors":"Yejian Chen, T. Wild, F. Schaich","doi":"10.1109/ICCCHINA.2014.7008336","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate channel estimation for Interleave-Division Multiple Access (IDMA) in an asynchronous multiuser system, by deploying superimposed pilots. As the superimposed pilots are the a priori known spreading sequences, the initial channel estimates can be obtained by separating the users with respect to the corresponding code-division orthogonality. Within the inherent IDMA iterations, a trellis-based channel estimator is integrated, which can significantly enhance the channel estimation during the iterations, by exploiting the superimposed pilots. Notice that the so-called turbo-effect can be clearly observed, in which both data detection and channel estimation are jointly improved between consecutive iterations.","PeriodicalId":353402,"journal":{"name":"2014 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Trellis-based channel estimation for asynchronous IDMA with superimposed pilots\",\"authors\":\"Yejian Chen, T. Wild, F. Schaich\",\"doi\":\"10.1109/ICCCHINA.2014.7008336\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we investigate channel estimation for Interleave-Division Multiple Access (IDMA) in an asynchronous multiuser system, by deploying superimposed pilots. As the superimposed pilots are the a priori known spreading sequences, the initial channel estimates can be obtained by separating the users with respect to the corresponding code-division orthogonality. Within the inherent IDMA iterations, a trellis-based channel estimator is integrated, which can significantly enhance the channel estimation during the iterations, by exploiting the superimposed pilots. Notice that the so-called turbo-effect can be clearly observed, in which both data detection and channel estimation are jointly improved between consecutive iterations.\",\"PeriodicalId\":353402,\"journal\":{\"name\":\"2014 IEEE/CIC International Conference on Communications in China (ICCC)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE/CIC International Conference on Communications in China (ICCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCHINA.2014.7008336\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE/CIC International Conference on Communications in China (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCHINA.2014.7008336","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Trellis-based channel estimation for asynchronous IDMA with superimposed pilots
In this paper, we investigate channel estimation for Interleave-Division Multiple Access (IDMA) in an asynchronous multiuser system, by deploying superimposed pilots. As the superimposed pilots are the a priori known spreading sequences, the initial channel estimates can be obtained by separating the users with respect to the corresponding code-division orthogonality. Within the inherent IDMA iterations, a trellis-based channel estimator is integrated, which can significantly enhance the channel estimation during the iterations, by exploiting the superimposed pilots. Notice that the so-called turbo-effect can be clearly observed, in which both data detection and channel estimation are jointly improved between consecutive iterations.