{"title":"低功耗数字滤波的自适应误差抵消","authors":"Lei Wang, N. Shanbhag","doi":"10.1109/ACSSC.2000.911279","DOIUrl":null,"url":null,"abstract":"This paper presents a low-power digital filtering technique derived via algorithmic noise-tolerance (ANT). The proposed technique achieves substantial energy savings via voltage overscaling (VOS), where the supply voltage is scaled beyond the minimum (referred to as V/sub dd-crit/) necessary for correct operation. The resulting performance degradation is compensated for via an adaptive error-cancellation (AEC) algorithm. In particular, we employ an energy optimum AEC to optimize the energy-performance trade-off and reduce the overhead due to ANT. It is shown that the proposed AEC technique is well-suited for designing low-power broadband signal processing and communication systems. Up to 71% energy savings over optimally voltage-scaled conventional systems can be obtained in the context of frequency-division multiplexed (FDM) communications without incurring any performance loss.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"7 1","pages":"1702-1706 vol.2"},"PeriodicalIF":0.0000,"publicationDate":"2000-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Adaptive error-cancellation for low-power digital filtering\",\"authors\":\"Lei Wang, N. Shanbhag\",\"doi\":\"10.1109/ACSSC.2000.911279\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a low-power digital filtering technique derived via algorithmic noise-tolerance (ANT). The proposed technique achieves substantial energy savings via voltage overscaling (VOS), where the supply voltage is scaled beyond the minimum (referred to as V/sub dd-crit/) necessary for correct operation. The resulting performance degradation is compensated for via an adaptive error-cancellation (AEC) algorithm. In particular, we employ an energy optimum AEC to optimize the energy-performance trade-off and reduce the overhead due to ANT. It is shown that the proposed AEC technique is well-suited for designing low-power broadband signal processing and communication systems. Up to 71% energy savings over optimally voltage-scaled conventional systems can be obtained in the context of frequency-division multiplexed (FDM) communications without incurring any performance loss.\",\"PeriodicalId\":10581,\"journal\":{\"name\":\"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)\",\"volume\":\"7 1\",\"pages\":\"1702-1706 vol.2\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACSSC.2000.911279\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.2000.911279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive error-cancellation for low-power digital filtering
This paper presents a low-power digital filtering technique derived via algorithmic noise-tolerance (ANT). The proposed technique achieves substantial energy savings via voltage overscaling (VOS), where the supply voltage is scaled beyond the minimum (referred to as V/sub dd-crit/) necessary for correct operation. The resulting performance degradation is compensated for via an adaptive error-cancellation (AEC) algorithm. In particular, we employ an energy optimum AEC to optimize the energy-performance trade-off and reduce the overhead due to ANT. It is shown that the proposed AEC technique is well-suited for designing low-power broadband signal processing and communication systems. Up to 71% energy savings over optimally voltage-scaled conventional systems can be obtained in the context of frequency-division multiplexed (FDM) communications without incurring any performance loss.