基于粒子群遗传混合优化算法在OFDMA中自适应资源分配应用  

Application of Particle Swarm Genetic Hybrid Optimization Algorithm in Adaptive Resource Allocation in OFDMA

作　　者：荣国成 王昊[1] 沙莎 RONG Guo-cheng;WANG Hao;SHA Sha(School of Electronics and Information Engineering,Changchun University of Science and Technology,Changchun 130022;School of Electronic Engineering,Changchun College of Electronic Technology,Changchun 130114)

机构地区：[1]长春理工大学电子信息工程学院,长春130022 [2]长春电子科技学院电子工程学院,长春130114

出　　处：《长春理工大学学报（自然科学版）》2021年第3期96-101,共6页Journal of Changchun University of Science and Technology(Natural Science Edition)

基　　金：吉林省科技厅项目(20200403151SF)。

摘　　要：针对正交频分多址技术(OFDMA)在无线通信系统中资源分配不均衡导致无法满足用户服务质量问题,将OFDMA资源分配问题转化为函数优化问题,分别对子载波分配与功率分配进行研究,在传统粒子群算法与遗传算法基础上引用一种混合自适应算法对目标函数求取最佳解,对资源分配问题进行研究,目的在保证用户比例公平性的条件下提高有效资源利用率,最大化系统吞吐量。通过仿真分析表明,与其他算法相比,混合优化算法在系统公平性与吞吐量方面具有有效提高。For Orthogonal Frequency Division Multiple Access(OFDMA),the imbalanced resource allocation in wireless communication systems led to the inability to meet user service quality issues.In this paper,the OFDMA resource allocation problem was transformed into a function optimization problem;sub-carrier allocation and power allocation separately was studied based on traditional particle swarm optimization and genetic algorithm.A hybrid adaptive algorithm was used to find the best solution to the objective function,and the resource allocation problem is studied.The purpose was to improve the effective resource utilization and maximize the system throughput under the condition of ensuring the fairness of the user’s proportion.Simulation analysis showed that compared with other algorithms,the hybrid optimization algorithm had an effective improvement in system fairness and throughput.

关 键 词：无线通信 资源分配 吞吐量 粒子群算法 优化算法 

分 类 号：TN925[电子电信—通信与信息系统]