{"title":"Power Prediction of Multipath Components in Wireless MIMO Channels","authors":"D. Shutin, G. Kubin","doi":"10.1109/ICICS.2005.1689318","DOIUrl":null,"url":null,"abstract":"Wireless systems are subject to fading-time variations of the receiving conditions caused by multipath propagation and transceiver movements. Prediction of fading allows to 'learn' the channel state information (CSI) in advance and adjust the transmission scheme as required based on the future values of CSI. In this contribution we propose a framework to handle predictions of general fast- and non-flat fading MIMO wireless channels. Unlike current approaches to predict channels by feeding sampled channel impulse response taps into the predictor, we first estimate multipath parameters, such as delay, Doppler frequencies, DoD/DoA, and design predictors for them. This step decreases the rate of variation of the channel thus allowing a greater prediction horizon and simpler predictor designs. The extracted parameters are then tracked over time and multipath gains are predicted using a linear model that is recursively updated. The prediction scheme is applied to the measured MIMO impulse responses to demonstrate the applicability of the method","PeriodicalId":425178,"journal":{"name":"2005 5th International Conference on Information Communications & Signal Processing","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 5th International Conference on Information Communications & Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICS.2005.1689318","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Wireless systems are subject to fading-time variations of the receiving conditions caused by multipath propagation and transceiver movements. Prediction of fading allows to 'learn' the channel state information (CSI) in advance and adjust the transmission scheme as required based on the future values of CSI. In this contribution we propose a framework to handle predictions of general fast- and non-flat fading MIMO wireless channels. Unlike current approaches to predict channels by feeding sampled channel impulse response taps into the predictor, we first estimate multipath parameters, such as delay, Doppler frequencies, DoD/DoA, and design predictors for them. This step decreases the rate of variation of the channel thus allowing a greater prediction horizon and simpler predictor designs. The extracted parameters are then tracked over time and multipath gains are predicted using a linear model that is recursively updated. The prediction scheme is applied to the measured MIMO impulse responses to demonstrate the applicability of the method