{"title":"Achieving worst case robustness in energy efficient multiuser multicell cooperation systems","authors":"Yuke Cui, Wei Xu, Hua Zhang, X. You","doi":"10.1109/GlobalSIP.2014.7032082","DOIUrl":null,"url":null,"abstract":"This paper investigates robust energy efficient beam-forming for multi-cell downlink transmissions. A bounded uncertainty region is considered to model the impairments of channel state information (CSI) available at the base station (BS). We formulate the problem of beamforming optimization by maximizing the worst case energy efficiency (EE) under CSI uncertainties. Due to the non-convex nature of the problem, we resort to instead maximizing a lower bound to the primal objective function. In this way, the problem is casted to a convex semidefinite programming (SDP) under some specific conditions. We accordingly propose an alternating algorithm, which achieves a noticeable performance gain in terms of the worst case EE.","PeriodicalId":362306,"journal":{"name":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobalSIP.2014.7032082","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
This paper investigates robust energy efficient beam-forming for multi-cell downlink transmissions. A bounded uncertainty region is considered to model the impairments of channel state information (CSI) available at the base station (BS). We formulate the problem of beamforming optimization by maximizing the worst case energy efficiency (EE) under CSI uncertainties. Due to the non-convex nature of the problem, we resort to instead maximizing a lower bound to the primal objective function. In this way, the problem is casted to a convex semidefinite programming (SDP) under some specific conditions. We accordingly propose an alternating algorithm, which achieves a noticeable performance gain in terms of the worst case EE.