{"title":"Resource scheduling for HF reception based on improved ant colony optimization algorithm","authors":"Yang Liu, Lunwen Wang","doi":"10.1109/IAEAC.2017.8054423","DOIUrl":null,"url":null,"abstract":"Because of the many and dense signals in high frequency (HF) band, the complex electromagnetic environment and relatively limited resources, the efficiency of HF reception is not high. To solve this problem, a resource scheduling method for HF reception based on improved ant colony optimization (ACO) algorithm was proposed to reach cooperative HF reception. The parameter values of the ant colony optimization algorithm was optimized based on particle swarm optimization (PSO) thought, the new pheromone update method was presented, which combines the global asynchronous feature and elitist strategy to avoid the defects of the optimization algorithm such as slowly to converge and easily to fall into local optimum. The simulation experiments showed that the algorithm mentioned is not only able to get an effective solution, but also can significantly improve the convergence speed.","PeriodicalId":432109,"journal":{"name":"2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAEAC.2017.8054423","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Because of the many and dense signals in high frequency (HF) band, the complex electromagnetic environment and relatively limited resources, the efficiency of HF reception is not high. To solve this problem, a resource scheduling method for HF reception based on improved ant colony optimization (ACO) algorithm was proposed to reach cooperative HF reception. The parameter values of the ant colony optimization algorithm was optimized based on particle swarm optimization (PSO) thought, the new pheromone update method was presented, which combines the global asynchronous feature and elitist strategy to avoid the defects of the optimization algorithm such as slowly to converge and easily to fall into local optimum. The simulation experiments showed that the algorithm mentioned is not only able to get an effective solution, but also can significantly improve the convergence speed.