{"title":"数字接收机信噪比估计器的性能分析","authors":"Yunfei Chen, N. Beaulieu","doi":"10.1109/PACRIM.2005.1517305","DOIUrl":null,"url":null,"abstract":"The performances of the maximum likelihood (ML) signal-to-noise ratio (SNR) estimators developed in a companion paper [NC Beaulieu et al, 2005] are examined. Approximations to the probability density functions of the ML SNR estimates in a sampled signal processing receiver as well as a continuous time signal processing receiver are derived. Two measures of signal-to-noise ratio are studied in detail. The results are general and apply to both static additive white Gaussian noise channels and slowly fading channels.","PeriodicalId":346880,"journal":{"name":"PACRIM. 2005 IEEE Pacific Rim Conference on Communications, Computers and signal Processing, 2005.","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance analysis of SNR estimators in digital receivers\",\"authors\":\"Yunfei Chen, N. Beaulieu\",\"doi\":\"10.1109/PACRIM.2005.1517305\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The performances of the maximum likelihood (ML) signal-to-noise ratio (SNR) estimators developed in a companion paper [NC Beaulieu et al, 2005] are examined. Approximations to the probability density functions of the ML SNR estimates in a sampled signal processing receiver as well as a continuous time signal processing receiver are derived. Two measures of signal-to-noise ratio are studied in detail. The results are general and apply to both static additive white Gaussian noise channels and slowly fading channels.\",\"PeriodicalId\":346880,\"journal\":{\"name\":\"PACRIM. 2005 IEEE Pacific Rim Conference on Communications, Computers and signal Processing, 2005.\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PACRIM. 2005 IEEE Pacific Rim Conference on Communications, Computers and signal Processing, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PACRIM.2005.1517305\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PACRIM. 2005 IEEE Pacific Rim Conference on Communications, Computers and signal Processing, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACRIM.2005.1517305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
本文检验了同伴论文[NC Beaulieu et al ., 2005]中开发的最大似然(ML)信噪比(SNR)估计器的性能。导出了采样信号处理接收机和连续时间信号处理接收机中ML信噪比估计的概率密度函数的近似值。详细研究了信噪比的两种测量方法。结果具有普遍性,既适用于静态加性高斯白噪声信道,也适用于慢衰落信道。
Performance analysis of SNR estimators in digital receivers
The performances of the maximum likelihood (ML) signal-to-noise ratio (SNR) estimators developed in a companion paper [NC Beaulieu et al, 2005] are examined. Approximations to the probability density functions of the ML SNR estimates in a sampled signal processing receiver as well as a continuous time signal processing receiver are derived. Two measures of signal-to-noise ratio are studied in detail. The results are general and apply to both static additive white Gaussian noise channels and slowly fading channels.