{"title":"改进收敛时间和能量消耗的频偏估计","authors":"M. J. Ammer, J. Rabaey","doi":"10.1109/ISSSTA.2004.1371770","DOIUrl":null,"url":null,"abstract":"An approach to simultaneously improve the energy consumption and convergence time (given the input SNR and required estimation variance) of feedforward data-aided frequency estimation is presented. Four well-known frequency estimation algorithms are compared using actual ASIC hardware implementations to verify the results. It is demonstrated how a modification to the algorithms can simultaneously achieve lower energy consumption and improved convergence time. For example, for an input SNR of 12 dB and required estimation variance of 2/spl times/10/sup -5/, convergence time is decreased by a factor of 4 while decreasing the energy consumption by a factor of 4.3. Directions on how to apply these algorithms to spread spectrum systems are provided.","PeriodicalId":340769,"journal":{"name":"Eighth IEEE International Symposium on Spread Spectrum Techniques and Applications - Programme and Book of Abstracts (IEEE Cat. No.04TH8738)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Frequency offset estimation with improved convergence time and energy consumption\",\"authors\":\"M. J. Ammer, J. Rabaey\",\"doi\":\"10.1109/ISSSTA.2004.1371770\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An approach to simultaneously improve the energy consumption and convergence time (given the input SNR and required estimation variance) of feedforward data-aided frequency estimation is presented. Four well-known frequency estimation algorithms are compared using actual ASIC hardware implementations to verify the results. It is demonstrated how a modification to the algorithms can simultaneously achieve lower energy consumption and improved convergence time. For example, for an input SNR of 12 dB and required estimation variance of 2/spl times/10/sup -5/, convergence time is decreased by a factor of 4 while decreasing the energy consumption by a factor of 4.3. Directions on how to apply these algorithms to spread spectrum systems are provided.\",\"PeriodicalId\":340769,\"journal\":{\"name\":\"Eighth IEEE International Symposium on Spread Spectrum Techniques and Applications - Programme and Book of Abstracts (IEEE Cat. No.04TH8738)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Eighth IEEE International Symposium on Spread Spectrum Techniques and Applications - Programme and Book of Abstracts (IEEE Cat. No.04TH8738)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSSTA.2004.1371770\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eighth IEEE International Symposium on Spread Spectrum Techniques and Applications - Programme and Book of Abstracts (IEEE Cat. No.04TH8738)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSSTA.2004.1371770","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Frequency offset estimation with improved convergence time and energy consumption
An approach to simultaneously improve the energy consumption and convergence time (given the input SNR and required estimation variance) of feedforward data-aided frequency estimation is presented. Four well-known frequency estimation algorithms are compared using actual ASIC hardware implementations to verify the results. It is demonstrated how a modification to the algorithms can simultaneously achieve lower energy consumption and improved convergence time. For example, for an input SNR of 12 dB and required estimation variance of 2/spl times/10/sup -5/, convergence time is decreased by a factor of 4 while decreasing the energy consumption by a factor of 4.3. Directions on how to apply these algorithms to spread spectrum systems are provided.