Shuhang Wu, Shuangqing Wei, Yue Wang, R. Vaidyanathan, Jian Yuan
{"title":"Achievable partition information rate over noisy multi-access Boolean channel","authors":"Shuhang Wu, Shuangqing Wei, Yue Wang, R. Vaidyanathan, Jian Yuan","doi":"10.1109/ISIT.2014.6875024","DOIUrl":null,"url":null,"abstract":"In this paper, we formulate a novel problem to quantify the amount of information transferred to partition active users who transmit following a common codebook over noisy Boolean multi-access channels. The objective of transmission is to ultimately let each active user aware of its own group only, not others. To solve the problem, we propose a novel framework by considering the decoding as a process of removing hyperedges of a complete hypergraph. For a particular, but non-trivial, case with two active users, an achievable bound for the defined partition information rate is found by using strong typical set decoding, as well as a large deviation technique for an induced Markov chain.","PeriodicalId":127191,"journal":{"name":"2014 IEEE International Symposium on Information Theory","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Symposium on Information Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIT.2014.6875024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
In this paper, we formulate a novel problem to quantify the amount of information transferred to partition active users who transmit following a common codebook over noisy Boolean multi-access channels. The objective of transmission is to ultimately let each active user aware of its own group only, not others. To solve the problem, we propose a novel framework by considering the decoding as a process of removing hyperedges of a complete hypergraph. For a particular, but non-trivial, case with two active users, an achievable bound for the defined partition information rate is found by using strong typical set decoding, as well as a large deviation technique for an induced Markov chain.