{"title":"非高斯定权分布的递归单奇偶校验积码","authors":"In Jun Park, Tong-sok Kim, Y. C. Kim","doi":"10.1109/ATNAC.2008.4783312","DOIUrl":null,"url":null,"abstract":"In iterated product of single parity check (SPC) codes, weight distribution is an important factor for the performance against transmission errors. A product code with Gaussian weight distribution should have a good performance. We present a closed-form solution for the weight distribution of a recursive SPC product code. We show that the code weights for this code are symmetrically distributed at (N plusmn radic(N)/2), where N is the full-length of a codeword. Though this code does not have a Gaussian weight distribution, it has better performance than conventional product codes. When soft-output iterative decoding is applied, the performance is away from the Shannon capacity limit by only 0.95 dB. Hence, we conclude that Gaussian weight distribution is not a necessary condition for a good performance.","PeriodicalId":143803,"journal":{"name":"2008 Australasian Telecommunication Networks and Applications Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Recursive Single Parity Check Product Code with Non-Gaussian Fixed Weight Distribution\",\"authors\":\"In Jun Park, Tong-sok Kim, Y. C. Kim\",\"doi\":\"10.1109/ATNAC.2008.4783312\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In iterated product of single parity check (SPC) codes, weight distribution is an important factor for the performance against transmission errors. A product code with Gaussian weight distribution should have a good performance. We present a closed-form solution for the weight distribution of a recursive SPC product code. We show that the code weights for this code are symmetrically distributed at (N plusmn radic(N)/2), where N is the full-length of a codeword. Though this code does not have a Gaussian weight distribution, it has better performance than conventional product codes. When soft-output iterative decoding is applied, the performance is away from the Shannon capacity limit by only 0.95 dB. Hence, we conclude that Gaussian weight distribution is not a necessary condition for a good performance.\",\"PeriodicalId\":143803,\"journal\":{\"name\":\"2008 Australasian Telecommunication Networks and Applications Conference\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Australasian Telecommunication Networks and Applications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ATNAC.2008.4783312\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Australasian Telecommunication Networks and Applications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATNAC.2008.4783312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Recursive Single Parity Check Product Code with Non-Gaussian Fixed Weight Distribution
In iterated product of single parity check (SPC) codes, weight distribution is an important factor for the performance against transmission errors. A product code with Gaussian weight distribution should have a good performance. We present a closed-form solution for the weight distribution of a recursive SPC product code. We show that the code weights for this code are symmetrically distributed at (N plusmn radic(N)/2), where N is the full-length of a codeword. Though this code does not have a Gaussian weight distribution, it has better performance than conventional product codes. When soft-output iterative decoding is applied, the performance is away from the Shannon capacity limit by only 0.95 dB. Hence, we conclude that Gaussian weight distribution is not a necessary condition for a good performance.