{"title":"一种基于序数的OFDM整数频偏估计方法","authors":"Xinxin Liu, Zhan Xu, Lu Tian, Xiaolong Yang","doi":"10.1109/IC-NIDC54101.2021.9660588","DOIUrl":null,"url":null,"abstract":"Orthogonal frequency division multiplexing (OFDM) is very sensitive to frequency offset. Although the existence of integer frequency offset in OFDM will not destroy the orthogonality between subcarriers, it will cause a cyclic shift of the frequency domain data after FFT transformation at the receiving end, which will affect the demodulation of data. In this paper, we propose a novel integer frequency offset estimation method based on the similarity property of adjacent subcarriers of the preamble. This method not only guarantees the original accuracy and performance of the conventional method but also achieves less resource consumption and lower computational complexity.","PeriodicalId":264468,"journal":{"name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Integer Frequency Offset Estimation Method for OFDM Based on Preamble\",\"authors\":\"Xinxin Liu, Zhan Xu, Lu Tian, Xiaolong Yang\",\"doi\":\"10.1109/IC-NIDC54101.2021.9660588\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Orthogonal frequency division multiplexing (OFDM) is very sensitive to frequency offset. Although the existence of integer frequency offset in OFDM will not destroy the orthogonality between subcarriers, it will cause a cyclic shift of the frequency domain data after FFT transformation at the receiving end, which will affect the demodulation of data. In this paper, we propose a novel integer frequency offset estimation method based on the similarity property of adjacent subcarriers of the preamble. This method not only guarantees the original accuracy and performance of the conventional method but also achieves less resource consumption and lower computational complexity.\",\"PeriodicalId\":264468,\"journal\":{\"name\":\"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IC-NIDC54101.2021.9660588\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC-NIDC54101.2021.9660588","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Integer Frequency Offset Estimation Method for OFDM Based on Preamble
Orthogonal frequency division multiplexing (OFDM) is very sensitive to frequency offset. Although the existence of integer frequency offset in OFDM will not destroy the orthogonality between subcarriers, it will cause a cyclic shift of the frequency domain data after FFT transformation at the receiving end, which will affect the demodulation of data. In this paper, we propose a novel integer frequency offset estimation method based on the similarity property of adjacent subcarriers of the preamble. This method not only guarantees the original accuracy and performance of the conventional method but also achieves less resource consumption and lower computational complexity.