{"title":"Multi-base station cooperation downlink statistical eigenmode transmission","authors":"Jun Zhang, Bin Jiang, Shi Jin, Xiqi Gao","doi":"10.1109/WCSP.2010.5633518","DOIUrl":null,"url":null,"abstract":"This paper investigates the downlink transmission for cooperative cellular networks with multi-base stations and single mobile station using statistical channel state information at the base stations. We consider a general jointly correlated MIMO channel model. We first propose an optimal transmission scheme to maximize the ergodic sum capacity, which reveals the transmit signals of all base stations are mutual independent and the optimal signaling directions are the eigenvectors of the transmit correlation matrix of the MIMO channel. Then we employ the matrix permanents to derive a closed-form tight upper bound for the ergodic sum capacity. Based on these results, we develop a low-complexity power allocation solution using convex optimization techniques and a simple iterative water-filling algorithm. Simulations demonstrate the upper bound of ergodic sum capacity is tight and the cooperative base stations transmission schemes increase the downlink system sum capacity.","PeriodicalId":448094,"journal":{"name":"2010 International Conference on Wireless Communications & Signal Processing (WCSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Wireless Communications & Signal Processing (WCSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCSP.2010.5633518","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper investigates the downlink transmission for cooperative cellular networks with multi-base stations and single mobile station using statistical channel state information at the base stations. We consider a general jointly correlated MIMO channel model. We first propose an optimal transmission scheme to maximize the ergodic sum capacity, which reveals the transmit signals of all base stations are mutual independent and the optimal signaling directions are the eigenvectors of the transmit correlation matrix of the MIMO channel. Then we employ the matrix permanents to derive a closed-form tight upper bound for the ergodic sum capacity. Based on these results, we develop a low-complexity power allocation solution using convex optimization techniques and a simple iterative water-filling algorithm. Simulations demonstrate the upper bound of ergodic sum capacity is tight and the cooperative base stations transmission schemes increase the downlink system sum capacity.