{"title":"基于高斯投影平均的MIMO检测","authors":"J. Goldberger","doi":"10.1109/ICASSP.2014.6853932","DOIUrl":null,"url":null,"abstract":"We propose a new detection algorithm for MIMO communication systems employing a two-dimensional marginal of the Gaussian approximation of the exact discrete distribution of the transmitted data given the received data. From the 2D distributions we derive one-dimensional marginals by averaging all the 2D joint distributions related to a single input symbol. We prove that this strategy to obtain a 1D distribution from a set of not necessarily consistent 2D distributions is optimal (for a specified criterion). The improved performance of the proposed algorithm is demonstrated on several instances of the problem of MIMO detection.","PeriodicalId":6545,"journal":{"name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"38 1","pages":"1916-1920"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"MIMO detection based on averaging Gaussian projections\",\"authors\":\"J. Goldberger\",\"doi\":\"10.1109/ICASSP.2014.6853932\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a new detection algorithm for MIMO communication systems employing a two-dimensional marginal of the Gaussian approximation of the exact discrete distribution of the transmitted data given the received data. From the 2D distributions we derive one-dimensional marginals by averaging all the 2D joint distributions related to a single input symbol. We prove that this strategy to obtain a 1D distribution from a set of not necessarily consistent 2D distributions is optimal (for a specified criterion). The improved performance of the proposed algorithm is demonstrated on several instances of the problem of MIMO detection.\",\"PeriodicalId\":6545,\"journal\":{\"name\":\"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)\",\"volume\":\"38 1\",\"pages\":\"1916-1920\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.2014.6853932\",\"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 International Conference on Acoustics, Speech and Signal Processing (ICASSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2014.6853932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MIMO detection based on averaging Gaussian projections
We propose a new detection algorithm for MIMO communication systems employing a two-dimensional marginal of the Gaussian approximation of the exact discrete distribution of the transmitted data given the received data. From the 2D distributions we derive one-dimensional marginals by averaging all the 2D joint distributions related to a single input symbol. We prove that this strategy to obtain a 1D distribution from a set of not necessarily consistent 2D distributions is optimal (for a specified criterion). The improved performance of the proposed algorithm is demonstrated on several instances of the problem of MIMO detection.