Jianwei Liu, Wei Guan, Jiang Wu, Zhen Tian, Wanlin Li
{"title":"Power allocation for energy efficiency maximization in DAS with hybrid rate constraint","authors":"Jianwei Liu, Wei Guan, Jiang Wu, Zhen Tian, Wanlin Li","doi":"10.1109/PIMRC.2015.7343564","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate the power allocation for energy efficiency (EE) maximization in distributed antenna systems (DAS) constrained by the hybrid minimum rate requirement. The optimization problem to maximize EE is non-convex. However, an equivalent convex optimization problem can be obtained from the original non-convex optimization problem using nonlinear fractional programming. Due to the convexity of the transformational problem, the solution gap approaches to zero when compared with its dual problem. Consequently, an iterative power allocation algorithm can be derived by solving the Karush-Kuhn-Tucker conditions of the dual problem. Simulation results demonstrate that the EE performance of the proposed algorithm outperforms rate adaptive power allocation scheme.","PeriodicalId":274734,"journal":{"name":"2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)","volume":"534 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","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.2015.7343564","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, we investigate the power allocation for energy efficiency (EE) maximization in distributed antenna systems (DAS) constrained by the hybrid minimum rate requirement. The optimization problem to maximize EE is non-convex. However, an equivalent convex optimization problem can be obtained from the original non-convex optimization problem using nonlinear fractional programming. Due to the convexity of the transformational problem, the solution gap approaches to zero when compared with its dual problem. Consequently, an iterative power allocation algorithm can be derived by solving the Karush-Kuhn-Tucker conditions of the dual problem. Simulation results demonstrate that the EE performance of the proposed algorithm outperforms rate adaptive power allocation scheme.