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基于鸽群算法的移动异构网络通信资源分配方法 被引量:1

Communication Resource Allocation Method for Mobile Heterogeneous Networks Based on Pigeon Swarm Algorithm
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摘要 针对在通信资源分配方案设定过程中忽视网络动态性,导致资源分配过程能效较高且用户资源获取量公平性较低的问题,提出基于鸽群算法的移动异构网络通信资源分配方法。将异构通信网络的组成部分分割为一个宏小区以及多个微小区,构建异构通信网络模型,为后续的研究提供基础。选择网络的数据吞吐量与能效值作为移动异构网络通信资源分配的目标函数,根据目标函数使用鸽群算法,求解通信资源分配方案的设计与优化。构建实验环节,分析此方法的应用效果。实验结果表明:该方法具有降低资源分配过程能效,提升用户资源获取量公平性和通信业务平均效用的作用。可为日后移动异构网络通信资源分配技术的发展寻找新方向。 Aiming at the problem that the setting process of communication resource allocation scheme ignores the network dynamics,which leads to the higher energy efficiency and the lower fairness of user resource acquisition in the resource allocation process,a communication resource allocation method based on pigeon colony algorithm is proposed for mobile heterogeneous networks.Divide the components of heterogeneous communication network into a macro cell and multiple micro cells,and build a heterogeneous communication network model to provide the basis for subsequent research.The data throughput and energy efficiency value of the network are selected as the objective function of communication resource allocation in mobile heterogeneous networks.According to the objective function,the pigeon swarm algorithm is used to solve the design and optimization of communication resource allocation scheme.Construct the experimental link and analyze the application effect of this method.The experimental results show that this method can reduce the energy efficiency of resource allocation process,improve the fairness of user resource acquisition,and improve the average utility of communication services.It can provide a new direction for the development of mobile heterogeneous network communication resource allocation technology in the future.
作者 陈竦 CHEN Song(Fuzhou Software Technology Vocational College,Fuzhou 350200,China)
出处 《长春工程学院学报(自然科学版)》 2022年第3期105-109,共5页 Journal of Changchun Institute of Technology:Natural Sciences Edition
关键词 鸽群算法 移动异构网络 通信资源分配 自适应参数 多目标优化算法 资源联合分配 pigeon swarm algorithm mobile heterogeneous network communication resource allocation adaptive parameters multi-objective optimization algorithm joint allocation of resources
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