{"title":"基于蒙特卡罗仿真的极码密度演化实现","authors":"Nobuhiko Miki;Satoshi Suyama;Satoshi Nagata","doi":"10.23919/comex.2025XBL0044","DOIUrl":null,"url":null,"abstract":"Density evolution (DE) plays a fundamental role in the analysis of channel coding systems employing iterative decoding, and it is a valuable tool to design such systems. This letter discusses the implementation of DE for polar codes. In this letter, fast Fourier transform based methods are difficult to apply due to the difficulty in optimizing the parameters, and therefore, DE is performed using a Monte Carlo simulation. Finally, examples of the applications of this method are presented.","PeriodicalId":54101,"journal":{"name":"IEICE Communications Express","volume":"14 6","pages":"250-253"},"PeriodicalIF":0.3000,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10964027","citationCount":"0","resultStr":"{\"title\":\"Implementation of Density Evolution for Polar Codes Based on Monte Carlo Simulation\",\"authors\":\"Nobuhiko Miki;Satoshi Suyama;Satoshi Nagata\",\"doi\":\"10.23919/comex.2025XBL0044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Density evolution (DE) plays a fundamental role in the analysis of channel coding systems employing iterative decoding, and it is a valuable tool to design such systems. This letter discusses the implementation of DE for polar codes. In this letter, fast Fourier transform based methods are difficult to apply due to the difficulty in optimizing the parameters, and therefore, DE is performed using a Monte Carlo simulation. Finally, examples of the applications of this method are presented.\",\"PeriodicalId\":54101,\"journal\":{\"name\":\"IEICE Communications Express\",\"volume\":\"14 6\",\"pages\":\"250-253\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2025-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10964027\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEICE Communications Express\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10964027/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEICE Communications Express","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10964027/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Implementation of Density Evolution for Polar Codes Based on Monte Carlo Simulation
Density evolution (DE) plays a fundamental role in the analysis of channel coding systems employing iterative decoding, and it is a valuable tool to design such systems. This letter discusses the implementation of DE for polar codes. In this letter, fast Fourier transform based methods are difficult to apply due to the difficulty in optimizing the parameters, and therefore, DE is performed using a Monte Carlo simulation. Finally, examples of the applications of this method are presented.
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