{"title":"信道极化的位信道研究","authors":"Wen-Yao Chen, Chung-Chin Lu","doi":"10.1109/ISIT50566.2022.9834393","DOIUrl":null,"url":null,"abstract":"The problem of constructing polar codes is equivalent to selecting good channels among a set of bit-channels with output alphabet size grows exponentially. To solve the problem, Tal and Vardy proposed a channel quantization algorithm to approximate the original channel by channels with less output symbols. Based on Arıkan’s original work, we derived a matrix form of channel transformation. This formulation automatically merges suitable output symbols, thus reducing the step of preprocessing complexity in Tal and Vardy’s algorithm.","PeriodicalId":348168,"journal":{"name":"2022 IEEE International Symposium on Information Theory (ISIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On the Bit-Channels for Channel Polarization\",\"authors\":\"Wen-Yao Chen, Chung-Chin Lu\",\"doi\":\"10.1109/ISIT50566.2022.9834393\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of constructing polar codes is equivalent to selecting good channels among a set of bit-channels with output alphabet size grows exponentially. To solve the problem, Tal and Vardy proposed a channel quantization algorithm to approximate the original channel by channels with less output symbols. Based on Arıkan’s original work, we derived a matrix form of channel transformation. This formulation automatically merges suitable output symbols, thus reducing the step of preprocessing complexity in Tal and Vardy’s algorithm.\",\"PeriodicalId\":348168,\"journal\":{\"name\":\"2022 IEEE International Symposium on Information Theory (ISIT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Symposium on Information Theory (ISIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIT50566.2022.9834393\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Symposium on Information Theory (ISIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIT50566.2022.9834393","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The problem of constructing polar codes is equivalent to selecting good channels among a set of bit-channels with output alphabet size grows exponentially. To solve the problem, Tal and Vardy proposed a channel quantization algorithm to approximate the original channel by channels with less output symbols. Based on Arıkan’s original work, we derived a matrix form of channel transformation. This formulation automatically merges suitable output symbols, thus reducing the step of preprocessing complexity in Tal and Vardy’s algorithm.