{"title":"基于人工神经网络的分组码软判决译码","authors":"S. El-Khamy, E. Youssef, H. Abdou","doi":"10.1109/SCAC.1995.523672","DOIUrl":null,"url":null,"abstract":"A soft decision decoder of linear block codes based on artificial neural networks (ANN) is presented. Various structures of the ANN decoder (ANND) are introduced and compared with the optimum soft-decision decoding (SDD) and hard-decision decoding (HDD) methods. Although the performance of the SDD is still optimum, the massive parallel nature of the neural network is shown to be more suitable to high data rate communication systems for which optimum decoding is impractical because of complexity and time consumption. The proposed ANND bridges the gap in performance and complexity between HDD and SDD. It is shown that the proposed receiver has superior performance in noisy channels with low signal to noise ratios.","PeriodicalId":90699,"journal":{"name":"Proceedings. IEEE Symposium on Computers and Communications","volume":"48 1","pages":"234-240"},"PeriodicalIF":0.0000,"publicationDate":"1995-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Soft decision decoding of block codes using artificial neural network\",\"authors\":\"S. El-Khamy, E. Youssef, H. Abdou\",\"doi\":\"10.1109/SCAC.1995.523672\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A soft decision decoder of linear block codes based on artificial neural networks (ANN) is presented. Various structures of the ANN decoder (ANND) are introduced and compared with the optimum soft-decision decoding (SDD) and hard-decision decoding (HDD) methods. Although the performance of the SDD is still optimum, the massive parallel nature of the neural network is shown to be more suitable to high data rate communication systems for which optimum decoding is impractical because of complexity and time consumption. The proposed ANND bridges the gap in performance and complexity between HDD and SDD. It is shown that the proposed receiver has superior performance in noisy channels with low signal to noise ratios.\",\"PeriodicalId\":90699,\"journal\":{\"name\":\"Proceedings. IEEE Symposium on Computers and Communications\",\"volume\":\"48 1\",\"pages\":\"234-240\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. IEEE Symposium on Computers and Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCAC.1995.523672\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE Symposium on Computers and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCAC.1995.523672","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Soft decision decoding of block codes using artificial neural network
A soft decision decoder of linear block codes based on artificial neural networks (ANN) is presented. Various structures of the ANN decoder (ANND) are introduced and compared with the optimum soft-decision decoding (SDD) and hard-decision decoding (HDD) methods. Although the performance of the SDD is still optimum, the massive parallel nature of the neural network is shown to be more suitable to high data rate communication systems for which optimum decoding is impractical because of complexity and time consumption. The proposed ANND bridges the gap in performance and complexity between HDD and SDD. It is shown that the proposed receiver has superior performance in noisy channels with low signal to noise ratios.