{"title":"同时同频全双工系统中基于频谱估计的数字自干扰消除算法","authors":"Yujie Li, Lingyun Sun, Caidan Zhao, Lianfeng Huang","doi":"10.1109/ICCSE.2015.7250280","DOIUrl":null,"url":null,"abstract":"In a Co-time Co-frequency Full-duplex (CCFD) system, the ability of Self-interference Cancellation (SIC) is limited if we use negative SIC or radio frequency SIC alone, so the residual Self-Interference Signal (SIS) needs to be further cancelled in digital domain. This paper proposed a digital Self-interference Cancellation algorithm based on spectral estimation, via establishing spectral estimation SIS model, we can analyze the spectrum of the SIS and digital transmitted signal. Then reconstruct the SIS and self-adaption cancellation via the second-order cyclic statistic information of signals. The simulation result shows that the proposed algorithm performance and convergence can effectively improved.","PeriodicalId":311451,"journal":{"name":"2015 10th International Conference on Computer Science & Education (ICCSE)","volume":"516 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A digital self-interference cancellation algorithm based on spectral estimation in co-time co-frequency full duplex system\",\"authors\":\"Yujie Li, Lingyun Sun, Caidan Zhao, Lianfeng Huang\",\"doi\":\"10.1109/ICCSE.2015.7250280\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a Co-time Co-frequency Full-duplex (CCFD) system, the ability of Self-interference Cancellation (SIC) is limited if we use negative SIC or radio frequency SIC alone, so the residual Self-Interference Signal (SIS) needs to be further cancelled in digital domain. This paper proposed a digital Self-interference Cancellation algorithm based on spectral estimation, via establishing spectral estimation SIS model, we can analyze the spectrum of the SIS and digital transmitted signal. Then reconstruct the SIS and self-adaption cancellation via the second-order cyclic statistic information of signals. The simulation result shows that the proposed algorithm performance and convergence can effectively improved.\",\"PeriodicalId\":311451,\"journal\":{\"name\":\"2015 10th International Conference on Computer Science & Education (ICCSE)\",\"volume\":\"516 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 10th International Conference on Computer Science & Education (ICCSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSE.2015.7250280\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 10th International Conference on Computer Science & Education (ICCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSE.2015.7250280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A digital self-interference cancellation algorithm based on spectral estimation in co-time co-frequency full duplex system
In a Co-time Co-frequency Full-duplex (CCFD) system, the ability of Self-interference Cancellation (SIC) is limited if we use negative SIC or radio frequency SIC alone, so the residual Self-Interference Signal (SIS) needs to be further cancelled in digital domain. This paper proposed a digital Self-interference Cancellation algorithm based on spectral estimation, via establishing spectral estimation SIS model, we can analyze the spectrum of the SIS and digital transmitted signal. Then reconstruct the SIS and self-adaption cancellation via the second-order cyclic statistic information of signals. The simulation result shows that the proposed algorithm performance and convergence can effectively improved.