{"title":"角域和延迟域传播参数的随机极大似然估计","authors":"C. Ribeiro, A. Richter, V. Koivunen","doi":"10.1109/PIMRC.2005.1651511","DOIUrl":null,"url":null,"abstract":"In this paper we derive an estimator for both time-delay and angular channel propagation parameters of the diffuse scattering component that is frequently observed in channel sounding measurements. The joint angular-delay model leads to correlation matrix with high dimensionality, which prevents direct implementation of a maximum-likelihood (ML) estimator using finite precision arithmetics and finite memory resources. We derive low complexity methods for computing the ML estimates that exploit the structure of the covariance matrices. The estimator is based on a two step procedure: first, the parameters of the power delay profile are estimated, as well as measurement noise power. Then, using the estimated time-delay parameters, the parameters of the angular distributions are estimated. We present simulation results and compare the estimated time-delay and angular distributions to the actual distributions, showing that high precision estimates are obtained","PeriodicalId":248766,"journal":{"name":"2005 IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Stochastic Maximum Likelihood Estimation of Angle- and Delay-Domain Propagation Parameters\",\"authors\":\"C. Ribeiro, A. Richter, V. Koivunen\",\"doi\":\"10.1109/PIMRC.2005.1651511\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we derive an estimator for both time-delay and angular channel propagation parameters of the diffuse scattering component that is frequently observed in channel sounding measurements. The joint angular-delay model leads to correlation matrix with high dimensionality, which prevents direct implementation of a maximum-likelihood (ML) estimator using finite precision arithmetics and finite memory resources. We derive low complexity methods for computing the ML estimates that exploit the structure of the covariance matrices. The estimator is based on a two step procedure: first, the parameters of the power delay profile are estimated, as well as measurement noise power. Then, using the estimated time-delay parameters, the parameters of the angular distributions are estimated. We present simulation results and compare the estimated time-delay and angular distributions to the actual distributions, showing that high precision estimates are obtained\",\"PeriodicalId\":248766,\"journal\":{\"name\":\"2005 IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PIMRC.2005.1651511\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIMRC.2005.1651511","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stochastic Maximum Likelihood Estimation of Angle- and Delay-Domain Propagation Parameters
In this paper we derive an estimator for both time-delay and angular channel propagation parameters of the diffuse scattering component that is frequently observed in channel sounding measurements. The joint angular-delay model leads to correlation matrix with high dimensionality, which prevents direct implementation of a maximum-likelihood (ML) estimator using finite precision arithmetics and finite memory resources. We derive low complexity methods for computing the ML estimates that exploit the structure of the covariance matrices. The estimator is based on a two step procedure: first, the parameters of the power delay profile are estimated, as well as measurement noise power. Then, using the estimated time-delay parameters, the parameters of the angular distributions are estimated. We present simulation results and compare the estimated time-delay and angular distributions to the actual distributions, showing that high precision estimates are obtained