摘要
针对认知无线电频谱分配优化算法寻优效果导致系统总效益低的问题,对于二进制萤火虫算法存在搜索易陷入局部最优的缺点,提出了一种融合Logistic映射的二进制萤火虫频谱分配策略。借助Logistic混沌映射,优化萤火虫算法位置更新公式的随机项——随机移动步长和随机数,并对优化结果加以修正,使算法快速跳出局部最优;以自适应的方式对萤火虫的位置进行二进制转换,增强算法运行初期的探索能力和运行后期的开发能力。仿真实验结果表明,本文算法的系统总效益较BFA、BPSO算法提高了8.19%和11.97%,可实现更高效的频谱分配。
Aiming at the problem that the searching effect of cognitive radio spectrum allocation optimization algorithm leads to the low total benefit of the system,we propose a binary firefly spectrum allocation strategy based on logistic mapping,because the binary firefly algorithm is prone to fall into the local optimum.Random moving step size and random number,as the random terms of position updating formula of the firefly algorithm,is optimized by the logistic mapping and the optimization results are modified to make the algorithm jump out of local optimum quickly;The binary conversion of firefly position is carried out in an adaptive way to enhance the exploration ability of the algorithm in the early stage and the development ability in the later stage.Simulation results show that compared with BFA and BPSO algorithms,the total system benefit of the proposed algorithm is improved by 8.19%and 11.97%respectively,and it can achieve more efficient spectrum allocation.
作者
滕志军
张华
张爱玲
韩忠廷
张恒嘉
TENG Zhi-jun;ZHANG Hua;ZHANG Ai-ling;HAN Zhong-ting;ZHANG Heng-jia(Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology,Ministry of Education,Northeast Electric Power University,Jilin 132012,China;School of Electrical Engineering,Northeast Electric Power University,Jilin 132012,China;College of Internet of ThingsEngineering,Hohai University,Nanjing 210018,China;College of Computer Science andTechnology,Jilin University,Changchun 130022,China)
出处
《哈尔滨理工大学学报》
CAS
北大核心
2022年第4期16-22,共7页
Journal of Harbin University of Science and Technology
基金
国家自然科学基金青年基金(61501107)
吉林省教育厅“十三五”科学研究规划项目(JJKH20180439KJ).
关键词
混沌映射
二进制萤火虫算法
频谱分配
认知用户
系统总效益
chaotic mapping
binary firefly algorithm
spectrum allocation
secondary user
total system benefit
