{"title":"Joint distributed source and network coding for correlated information multicasting","authors":"Shaoshuai Gao","doi":"10.1109/ChinaCom.2011.6158244","DOIUrl":null,"url":null,"abstract":"The problem of correlated information multicasting is considered in this paper, i.e., from multiple sources to multiple destinations through a network. It can be solved by jointly optimizing the distributed source coding and network coding. Previous research found that optimal performance can be achieved with unlimited decoding complexity, which cannot be applied in practical implementations. Some practical methods were also presented, which shows sub-optimal performance. To improve the coding performance and keep the low complexity of the algorithm, an adaptive coding and transmission scheme according to the conditional entropy of the sources is proposed. It has been demonstrated that the proposed scheme can achieve better performance compared with the existing ones.","PeriodicalId":339961,"journal":{"name":"2011 6th International ICST Conference on Communications and Networking in China (CHINACOM)","volume":"168 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 6th International ICST Conference on Communications and Networking in China (CHINACOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ChinaCom.2011.6158244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The problem of correlated information multicasting is considered in this paper, i.e., from multiple sources to multiple destinations through a network. It can be solved by jointly optimizing the distributed source coding and network coding. Previous research found that optimal performance can be achieved with unlimited decoding complexity, which cannot be applied in practical implementations. Some practical methods were also presented, which shows sub-optimal performance. To improve the coding performance and keep the low complexity of the algorithm, an adaptive coding and transmission scheme according to the conditional entropy of the sources is proposed. It has been demonstrated that the proposed scheme can achieve better performance compared with the existing ones.