{"title":"MSE-based orthogonal beamformer design for interference alignment in a MU-MIMO cellular network","authors":"M. Torabi, J. Frigon, C. Cardinal","doi":"10.1109/PIMRC.2011.6139833","DOIUrl":null,"url":null,"abstract":"In this paper we consider an Interference Alignment (IA) approach for intercell interference coordination for the downlink of a MIMO multi-user cellular network. We determine the maximum degrees of freedom (DoF) of the network and give the feasibility proof of perfect IA. Furthermore, we consider the problem of approximate IA and the Mean-Squared Error (MSE) based optimization of the transmit and receive beamforming matrices with the orthogonality constraints and the per-antenna transmit power constraint. Iterative algorithms are presented to solve the corresponding MSE problems. Simulation results and convergence analysis of the algorithms are also discussed. The results indicate that it is feasible to significantly increase the network capacity using the proposed IA approach.","PeriodicalId":262660,"journal":{"name":"2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIMRC.2011.6139833","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this paper we consider an Interference Alignment (IA) approach for intercell interference coordination for the downlink of a MIMO multi-user cellular network. We determine the maximum degrees of freedom (DoF) of the network and give the feasibility proof of perfect IA. Furthermore, we consider the problem of approximate IA and the Mean-Squared Error (MSE) based optimization of the transmit and receive beamforming matrices with the orthogonality constraints and the per-antenna transmit power constraint. Iterative algorithms are presented to solve the corresponding MSE problems. Simulation results and convergence analysis of the algorithms are also discussed. The results indicate that it is feasible to significantly increase the network capacity using the proposed IA approach.