{"title":"基于可动形状滤波器的数字自干扰消除算法","authors":"Haolong Wu, Yuwen Wang, Xuanrui Qu","doi":"10.1145/3387168.3387245","DOIUrl":null,"url":null,"abstract":"In digital self-inference cancellation field, the adaptive filter is the main way to eliminate self-interference. A mass of research is completed to optimize the performance of the adaptive algorithm. Nevertheless, we have noticed there are few scholars to modify the shape of the filter to achieve a better cancellation effect. Constrained by the fixed and immovable shape, the typical adaptive filter can't full use the information behind the digital signal. Stimulated by this problem, a lot of work have been fulfilled in order to acquire a more flexible filter shape. In this paper, we propose a novel filter architecture named as the movable shape filter. Through adding the position parameters to the typical filter, finer elimination results have been reached. Moreover, the rigorous simulation results show a great progress in the mean square error.","PeriodicalId":346739,"journal":{"name":"Proceedings of the 3rd International Conference on Vision, Image and Signal Processing","volume":"73 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Digital Self-interference Cancellation Algorithm Based on The Movable Shape Filter\",\"authors\":\"Haolong Wu, Yuwen Wang, Xuanrui Qu\",\"doi\":\"10.1145/3387168.3387245\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In digital self-inference cancellation field, the adaptive filter is the main way to eliminate self-interference. A mass of research is completed to optimize the performance of the adaptive algorithm. Nevertheless, we have noticed there are few scholars to modify the shape of the filter to achieve a better cancellation effect. Constrained by the fixed and immovable shape, the typical adaptive filter can't full use the information behind the digital signal. Stimulated by this problem, a lot of work have been fulfilled in order to acquire a more flexible filter shape. In this paper, we propose a novel filter architecture named as the movable shape filter. Through adding the position parameters to the typical filter, finer elimination results have been reached. Moreover, the rigorous simulation results show a great progress in the mean square error.\",\"PeriodicalId\":346739,\"journal\":{\"name\":\"Proceedings of the 3rd International Conference on Vision, Image and Signal Processing\",\"volume\":\"73 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 3rd International Conference on Vision, Image and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3387168.3387245\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd International Conference on Vision, Image and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3387168.3387245","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Digital Self-interference Cancellation Algorithm Based on The Movable Shape Filter
In digital self-inference cancellation field, the adaptive filter is the main way to eliminate self-interference. A mass of research is completed to optimize the performance of the adaptive algorithm. Nevertheless, we have noticed there are few scholars to modify the shape of the filter to achieve a better cancellation effect. Constrained by the fixed and immovable shape, the typical adaptive filter can't full use the information behind the digital signal. Stimulated by this problem, a lot of work have been fulfilled in order to acquire a more flexible filter shape. In this paper, we propose a novel filter architecture named as the movable shape filter. Through adding the position parameters to the typical filter, finer elimination results have been reached. Moreover, the rigorous simulation results show a great progress in the mean square error.