{"title":"Least squares end performance experiment design in multicarrier systems: The sparse preamble case","authors":"D. Katselis, C. Rojas, H. Hjalmarsson","doi":"10.1109/ECC.2014.6862346","DOIUrl":null,"url":null,"abstract":"In this paper, the problem of experiment design for the task of channel identification in cyclic prefixed orthogonal frequency division multiplexing (CP-OFDM) systems is revisited. So far, the optimal input sequences for least squares (LS) channel identification with respect to minimizing the channel mean square error (MSE) under an input energy constraint have been derived. Here, we investigate the same problem for the LS channel estimator, but when the design takes into account an end performance metric of interest, namely, the symbol estimate MSE. Based on some convex approximations, we verify that optimal sparse preambles, i.e, input vectors employing as many pilots as the channel length, for LS channel estimation in its classical context are near optimal in the aforementioned application-oriented context for the symbol estimate MSE.","PeriodicalId":251538,"journal":{"name":"2014 European Control Conference (ECC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 European Control Conference (ECC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECC.2014.6862346","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, the problem of experiment design for the task of channel identification in cyclic prefixed orthogonal frequency division multiplexing (CP-OFDM) systems is revisited. So far, the optimal input sequences for least squares (LS) channel identification with respect to minimizing the channel mean square error (MSE) under an input energy constraint have been derived. Here, we investigate the same problem for the LS channel estimator, but when the design takes into account an end performance metric of interest, namely, the symbol estimate MSE. Based on some convex approximations, we verify that optimal sparse preambles, i.e, input vectors employing as many pilots as the channel length, for LS channel estimation in its classical context are near optimal in the aforementioned application-oriented context for the symbol estimate MSE.