{"title":"基于人工鱼群算法的扩频码估计","authors":"M. Jiang, Yong Wang, F. Rubio, D. Yuan","doi":"10.1109/WISP.2007.4447587","DOIUrl":null,"url":null,"abstract":"A new estimation method by the swarm intelligent optimization algorithm is presented to recover the transmitted data bits and code of spread spectrum signal over additive white Gaussian noise channel, while the receiver has no knowledge of the transmitter spreading sequence, only knows the length of spreading sequence. The presented estimation method by Artificial Fish Swarm Algorithm (AFSA) is insensitive to initial values, has a strong robustness, and has the faster convergence speed and better estimation precision than the estimation method by Genetic Algorithm (GA) and the estimation method by Particle Swarm Optimization (PSO). The results show that the method can obtain the optimal or sub-optimal estimation of spreading code, even when the signal power is below the noise power.","PeriodicalId":164902,"journal":{"name":"2007 IEEE International Symposium on Intelligent Signal Processing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"39","resultStr":"{\"title\":\"Spread Spectrum Code Estimation by Artificial Fish Swarm Algorithm\",\"authors\":\"M. Jiang, Yong Wang, F. Rubio, D. Yuan\",\"doi\":\"10.1109/WISP.2007.4447587\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new estimation method by the swarm intelligent optimization algorithm is presented to recover the transmitted data bits and code of spread spectrum signal over additive white Gaussian noise channel, while the receiver has no knowledge of the transmitter spreading sequence, only knows the length of spreading sequence. The presented estimation method by Artificial Fish Swarm Algorithm (AFSA) is insensitive to initial values, has a strong robustness, and has the faster convergence speed and better estimation precision than the estimation method by Genetic Algorithm (GA) and the estimation method by Particle Swarm Optimization (PSO). The results show that the method can obtain the optimal or sub-optimal estimation of spreading code, even when the signal power is below the noise power.\",\"PeriodicalId\":164902,\"journal\":{\"name\":\"2007 IEEE International Symposium on Intelligent Signal Processing\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"39\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE International Symposium on Intelligent Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WISP.2007.4447587\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Symposium on Intelligent Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WISP.2007.4447587","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spread Spectrum Code Estimation by Artificial Fish Swarm Algorithm
A new estimation method by the swarm intelligent optimization algorithm is presented to recover the transmitted data bits and code of spread spectrum signal over additive white Gaussian noise channel, while the receiver has no knowledge of the transmitter spreading sequence, only knows the length of spreading sequence. The presented estimation method by Artificial Fish Swarm Algorithm (AFSA) is insensitive to initial values, has a strong robustness, and has the faster convergence speed and better estimation precision than the estimation method by Genetic Algorithm (GA) and the estimation method by Particle Swarm Optimization (PSO). The results show that the method can obtain the optimal or sub-optimal estimation of spreading code, even when the signal power is below the noise power.