{"title":"平坦衰落信道中一种改进的盲粒子滤波算法","authors":"Hongyan Zhang, Donghong Fan, Jinghai Bao","doi":"10.1109/APWCS.2010.72","DOIUrl":null,"url":null,"abstract":"An evolutionary particle filtering algorithm is proposed for blind signal detection in flat Rayleigh fading channels who’s model coefficients are unknown. The sample impoverishment of state boundaries without changing longtime can be relieved. The stochastic M-algorithm (SMA) is used to estimate the signal sent in flat fading channel. The simulation shows the proposed particle filtering algorithm upholds comparable performance with mixture Kalman filter.","PeriodicalId":354322,"journal":{"name":"2010 Asia-Pacific Conference on Wearable Computing Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Improved Blind Particle Filtering Algorithm in Flat Fading Channel\",\"authors\":\"Hongyan Zhang, Donghong Fan, Jinghai Bao\",\"doi\":\"10.1109/APWCS.2010.72\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An evolutionary particle filtering algorithm is proposed for blind signal detection in flat Rayleigh fading channels who’s model coefficients are unknown. The sample impoverishment of state boundaries without changing longtime can be relieved. The stochastic M-algorithm (SMA) is used to estimate the signal sent in flat fading channel. The simulation shows the proposed particle filtering algorithm upholds comparable performance with mixture Kalman filter.\",\"PeriodicalId\":354322,\"journal\":{\"name\":\"2010 Asia-Pacific Conference on Wearable Computing Systems\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Asia-Pacific Conference on Wearable Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APWCS.2010.72\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Asia-Pacific Conference on Wearable Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APWCS.2010.72","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Blind Particle Filtering Algorithm in Flat Fading Channel
An evolutionary particle filtering algorithm is proposed for blind signal detection in flat Rayleigh fading channels who’s model coefficients are unknown. The sample impoverishment of state boundaries without changing longtime can be relieved. The stochastic M-algorithm (SMA) is used to estimate the signal sent in flat fading channel. The simulation shows the proposed particle filtering algorithm upholds comparable performance with mixture Kalman filter.
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