{"title":"An extension to the chain graph representation of an achievable scheme","authors":"S. Rini","doi":"10.1109/ITW.2012.6404747","DOIUrl":null,"url":null,"abstract":"The chain graph representations of an achievable scheme is a recently introduced theoretical tool to derive achievable regions based on superposition coding and binning for a general, single-hop, multi-terminal network. It allows for a compact representation of complex transmission strategies and the derivation of the corresponding achievable region for a large class of channels. In this paper we extend the original concept to include a new random coding technique that generalizes superposition coding and binning. With this coding strategy, one generates a top codebook conditionally dependent on the bottom codeword and successively uses binning to impose a different conditional distribution between top and bottom codewords. The region achieved with this strategy relates to the Kullback-Leibler divergence between the distribution of the codewords at generation and the distribution after binning.","PeriodicalId":325771,"journal":{"name":"2012 IEEE Information Theory Workshop","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Information Theory Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITW.2012.6404747","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
The chain graph representations of an achievable scheme is a recently introduced theoretical tool to derive achievable regions based on superposition coding and binning for a general, single-hop, multi-terminal network. It allows for a compact representation of complex transmission strategies and the derivation of the corresponding achievable region for a large class of channels. In this paper we extend the original concept to include a new random coding technique that generalizes superposition coding and binning. With this coding strategy, one generates a top codebook conditionally dependent on the bottom codeword and successively uses binning to impose a different conditional distribution between top and bottom codewords. The region achieved with this strategy relates to the Kullback-Leibler divergence between the distribution of the codewords at generation and the distribution after binning.