{"title":"基于DVFS的AWGN信道LDPC解码器低功耗VLSI设计","authors":"Weihuang Wang, G. Choi, K. Gunnam","doi":"10.1109/VLSI.Design.2009.68","DOIUrl":null,"url":null,"abstract":"This paper presents a low-power LDPC decoder design for additive white Gaussian noise (AWGN) channels. The proposed decoding scheme provides constant-time decoding and thus facilitates real-time applications where guaranteed data rate is required. It analyzes each received data frame to estimate the maximum number of necessary iterations for frame convergence. The results are then used to dynamically adjust decoder frequency and switch between multiple-voltage levels; thereby energy use is minimized. It differs from recent publications on speculative LDPC decoding for block-fading channels. Our approach addresses the more difficult problem of decoding requirement prediction for data frames in AWGN channels. It is also directly applicable for fading channels. A decoder architecture utilizing offset min-sum layered decoding algorithm is presented. Up to 30% saving in decoding energy consumption is achieved with negligible coding performance degradation.","PeriodicalId":267121,"journal":{"name":"2009 22nd International Conference on VLSI Design","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Low-Power VLSI Design of LDPC Decoder Using DVFS for AWGN Channels\",\"authors\":\"Weihuang Wang, G. Choi, K. Gunnam\",\"doi\":\"10.1109/VLSI.Design.2009.68\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a low-power LDPC decoder design for additive white Gaussian noise (AWGN) channels. The proposed decoding scheme provides constant-time decoding and thus facilitates real-time applications where guaranteed data rate is required. It analyzes each received data frame to estimate the maximum number of necessary iterations for frame convergence. The results are then used to dynamically adjust decoder frequency and switch between multiple-voltage levels; thereby energy use is minimized. It differs from recent publications on speculative LDPC decoding for block-fading channels. Our approach addresses the more difficult problem of decoding requirement prediction for data frames in AWGN channels. It is also directly applicable for fading channels. A decoder architecture utilizing offset min-sum layered decoding algorithm is presented. Up to 30% saving in decoding energy consumption is achieved with negligible coding performance degradation.\",\"PeriodicalId\":267121,\"journal\":{\"name\":\"2009 22nd International Conference on VLSI Design\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-01-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 22nd International Conference on VLSI Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VLSI.Design.2009.68\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 22nd International Conference on VLSI Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VLSI.Design.2009.68","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Low-Power VLSI Design of LDPC Decoder Using DVFS for AWGN Channels
This paper presents a low-power LDPC decoder design for additive white Gaussian noise (AWGN) channels. The proposed decoding scheme provides constant-time decoding and thus facilitates real-time applications where guaranteed data rate is required. It analyzes each received data frame to estimate the maximum number of necessary iterations for frame convergence. The results are then used to dynamically adjust decoder frequency and switch between multiple-voltage levels; thereby energy use is minimized. It differs from recent publications on speculative LDPC decoding for block-fading channels. Our approach addresses the more difficult problem of decoding requirement prediction for data frames in AWGN channels. It is also directly applicable for fading channels. A decoder architecture utilizing offset min-sum layered decoding algorithm is presented. Up to 30% saving in decoding energy consumption is achieved with negligible coding performance degradation.