{"title":"Optimal transmission policy for collaborative beamforming with finite energy storage capacity","authors":"Lazar Berbakov, C. Antón-Haro, J. Matamoros","doi":"10.1109/PIMRC.2013.6666199","DOIUrl":null,"url":null,"abstract":"This paper considers a communication scenario where multiple energy harvesting sensors equipped with finite-capacity energy storage devices cooperate to transmit a previously shared common message to a distant base station. The goal is to identify the jointly optimal transmission (power allocation) policy which maximizes the total data throughput until a given deadline. To that aim, we propose a semi-analytical procedure on which basis the optimal policy for each sensor can be computed as a concatenation of a number of battery operated like transmission policies. The computational complexity of such semi-analytical methods turns out to be much lower than that of other numerical optimization tools (e.g., interior point algorithm). The performance is extensively assessed by means of computer simulations, with a specific emphasis on inter-senor distance, total amount of harvested energy and other system parameters. As a benchmark, we consider a strategy where the transmission policy is separately optimized for each sensor.","PeriodicalId":210993,"journal":{"name":"2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIMRC.2013.6666199","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper considers a communication scenario where multiple energy harvesting sensors equipped with finite-capacity energy storage devices cooperate to transmit a previously shared common message to a distant base station. The goal is to identify the jointly optimal transmission (power allocation) policy which maximizes the total data throughput until a given deadline. To that aim, we propose a semi-analytical procedure on which basis the optimal policy for each sensor can be computed as a concatenation of a number of battery operated like transmission policies. The computational complexity of such semi-analytical methods turns out to be much lower than that of other numerical optimization tools (e.g., interior point algorithm). The performance is extensively assessed by means of computer simulations, with a specific emphasis on inter-senor distance, total amount of harvested energy and other system parameters. As a benchmark, we consider a strategy where the transmission policy is separately optimized for each sensor.