{"title":"稀疏信道估计的改进贪婪算法","authors":"G. Lin, Xiaochuan Ma, Shefeng Yan, Jincheng Lin","doi":"10.1109/ICICIP.2015.7388173","DOIUrl":null,"url":null,"abstract":"Sparse channel estimation has attracted much attention these years, especially in the area of under water acoustic communication. Compressed sensing methods are popular recently because of their efficiency and stability. In this paper, a stable and fast algorithm termed Selective Regularized Orthogonal Matching Pursuit (SROMP) is proposed based on Orthogonal Matching Pursuit (OMP). By numerical experiments, performance of this algorithm is shown in comparison to conventional LS (least square) algorithm, basic OMP and Stagewise OMP. Simulation results indicate that this methods can estimate sparse channel effectively and accurately outperforming LS and OMP.","PeriodicalId":265426,"journal":{"name":"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An improved greedy algorithm for sparse channel estimation\",\"authors\":\"G. Lin, Xiaochuan Ma, Shefeng Yan, Jincheng Lin\",\"doi\":\"10.1109/ICICIP.2015.7388173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sparse channel estimation has attracted much attention these years, especially in the area of under water acoustic communication. Compressed sensing methods are popular recently because of their efficiency and stability. In this paper, a stable and fast algorithm termed Selective Regularized Orthogonal Matching Pursuit (SROMP) is proposed based on Orthogonal Matching Pursuit (OMP). By numerical experiments, performance of this algorithm is shown in comparison to conventional LS (least square) algorithm, basic OMP and Stagewise OMP. Simulation results indicate that this methods can estimate sparse channel effectively and accurately outperforming LS and OMP.\",\"PeriodicalId\":265426,\"journal\":{\"name\":\"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)\",\"volume\":\"100 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICIP.2015.7388173\",\"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 Sixth International Conference on Intelligent Control and Information Processing (ICICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICIP.2015.7388173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An improved greedy algorithm for sparse channel estimation
Sparse channel estimation has attracted much attention these years, especially in the area of under water acoustic communication. Compressed sensing methods are popular recently because of their efficiency and stability. In this paper, a stable and fast algorithm termed Selective Regularized Orthogonal Matching Pursuit (SROMP) is proposed based on Orthogonal Matching Pursuit (OMP). By numerical experiments, performance of this algorithm is shown in comparison to conventional LS (least square) algorithm, basic OMP and Stagewise OMP. Simulation results indicate that this methods can estimate sparse channel effectively and accurately outperforming LS and OMP.