{"title":"A novel joint channel and multi-user interference statistics estimator for UWB-IR based on Gaussian mixture model","authors":"V. Cellini, G. Doná","doi":"10.1109/ICU.2005.1570066","DOIUrl":null,"url":null,"abstract":"Ultra-wideband impulse radio communications have been growing rapidly over the last few years, as a promising technique for high bit-rate and multi-user transmissions over the 3-10 GHz unlicensed spectrum. In literature, multi-user interference is often approximated with a white Gaussian process and embodied in the overall noise term. However, it has been found that, in typical indoor environments, such approximation is inadequate. In this paper, we propose a new approach to characterize the interference, based on the Gaussian mixture model, which allows to derive a joint channel and multi-user interference statistics estimator, based on the iterative space-alternating generalized expectation maximization algorithm. The effectiveness of the proposed estimator is shown by means of numerical examples.","PeriodicalId":105819,"journal":{"name":"2005 IEEE International Conference on Ultra-Wideband","volume":"164 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 IEEE International Conference on Ultra-Wideband","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICU.2005.1570066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 37
Abstract
Ultra-wideband impulse radio communications have been growing rapidly over the last few years, as a promising technique for high bit-rate and multi-user transmissions over the 3-10 GHz unlicensed spectrum. In literature, multi-user interference is often approximated with a white Gaussian process and embodied in the overall noise term. However, it has been found that, in typical indoor environments, such approximation is inadequate. In this paper, we propose a new approach to characterize the interference, based on the Gaussian mixture model, which allows to derive a joint channel and multi-user interference statistics estimator, based on the iterative space-alternating generalized expectation maximization algorithm. The effectiveness of the proposed estimator is shown by means of numerical examples.