Haifan Yin, L. Cottatellucci, D. Gesbert, R. Müller, Gaoning He
{"title":"Pilot decontamination using combined angular and amplitude based projections in massive MIMO systems","authors":"Haifan Yin, L. Cottatellucci, D. Gesbert, R. Müller, Gaoning He","doi":"10.1109/SPAWC.2015.7227031","DOIUrl":null,"url":null,"abstract":"We address the problem of noise and interference corrupted channel estimation in massive MIMO systems. Interference, which originates from pilot reuse (or contamination), can in principle be discriminated from the desired channels upon observing the distributions of path angles and amplitudes. In this paper we propose novel robust channel estimation algorithms exploiting path diversity in both angle and amplitude domains, relying on a suitable combination of a subspace projection and MMSE estimation. The proposed estimator improves on past methods in a wide range of system and topology scenarios.","PeriodicalId":211324,"journal":{"name":"2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAWC.2015.7227031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
We address the problem of noise and interference corrupted channel estimation in massive MIMO systems. Interference, which originates from pilot reuse (or contamination), can in principle be discriminated from the desired channels upon observing the distributions of path angles and amplitudes. In this paper we propose novel robust channel estimation algorithms exploiting path diversity in both angle and amplitude domains, relying on a suitable combination of a subspace projection and MMSE estimation. The proposed estimator improves on past methods in a wide range of system and topology scenarios.