{"title":"Self-interference cancellation with phase-noise suppression in full-duplex systems","authors":"Ruozhu Li, A. Masmoudi, T. Le-Ngoc","doi":"10.1109/PIMRC.2015.7343306","DOIUrl":null,"url":null,"abstract":"In this paper, we focus on the self-interference (SI) cancellation in the presence of phase-noise in full-duplex systems. Reducing the SI needs the estimation of the SI channel and the phase-noise. In particular, the time-varying phase-noise process is approximated by an expansion over a basis. As the unknown intended signal received from the other transceiver can limit the estimation performance if considered as additive noise, we incorporate it in the joint estimation of the SI channel, the intended channel and the phase-noise process. The proposed algorithm maximizes the likelihood function by fully exploiting the known transmitted data and the second-order statistic of the intended signal.","PeriodicalId":274734,"journal":{"name":"2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIMRC.2015.7343306","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In this paper, we focus on the self-interference (SI) cancellation in the presence of phase-noise in full-duplex systems. Reducing the SI needs the estimation of the SI channel and the phase-noise. In particular, the time-varying phase-noise process is approximated by an expansion over a basis. As the unknown intended signal received from the other transceiver can limit the estimation performance if considered as additive noise, we incorporate it in the joint estimation of the SI channel, the intended channel and the phase-noise process. The proposed algorithm maximizes the likelihood function by fully exploiting the known transmitted data and the second-order statistic of the intended signal.