{"title":"Robust precoding with general power constraints considering unbounded channel uncertainty","authors":"R. Fritzsche, G. Fettweis","doi":"10.1109/ISWCS.2012.6328350","DOIUrl":null,"url":null,"abstract":"In this contribution we deal with a cooperative cellular downlink scenario, where collaborating base stations jointly serve multiple users in a multiple-input multiple-output fashion. Linear spatial signal processing filters are applied at transmitter and receiver. The filters are designed in order to optimize four different mean square error related objective functions, considering general power constraints, i.e., transmit power constraints per arbitrary group of antennas. This optimization is based on channel state information, which is only imperfectly known in practical setups. In this contribution, we present a filter design for the stated optimization problems, taking statistical knowledge of unbounded channel uncertainty into account.","PeriodicalId":167119,"journal":{"name":"2012 International Symposium on Wireless Communication Systems (ISWCS)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Symposium on Wireless Communication Systems (ISWCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISWCS.2012.6328350","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
In this contribution we deal with a cooperative cellular downlink scenario, where collaborating base stations jointly serve multiple users in a multiple-input multiple-output fashion. Linear spatial signal processing filters are applied at transmitter and receiver. The filters are designed in order to optimize four different mean square error related objective functions, considering general power constraints, i.e., transmit power constraints per arbitrary group of antennas. This optimization is based on channel state information, which is only imperfectly known in practical setups. In this contribution, we present a filter design for the stated optimization problems, taking statistical knowledge of unbounded channel uncertainty into account.