基于混合遗传算法的OFDMA资源分配方法  

OFDMA Resource Allocation Method Based on Hybrid Genetic Algorithm

作　　者：孙明[1] 翟康乐 曹伟[1] 张辉[1] SUN Ming;ZHAI Kang-le;CAO Wei;ZHANG Hui(College of Computer and Control Engineering,Qiqihar University,Qiqihar Heilongjiang 161006,China)

机构地区：[1]齐齐哈尔大学计算机与控制工程学院,黑龙江齐齐哈尔161006

出　　处：《计算机仿真》2023年第2期517-523,共7页Computer Simulation

基　　金：国家自然科学基金(61872204);黑龙江省自然科学基金(LH2019F038);黑龙江省高校基本科研业务专项(135309340)。

摘　　要：现有的OFDMA资源分配算法无法在保障公平度阈值的前提下有效地最大化系统和速率。针对上述问题,提出了一种基于混合遗传算法的OFDMA资源分配方法。首先将遗传算法的种群个体进行分组并为个体分组设置个体更新量,然后在此基础上采用贪婪子载波分配初始化种群个体,并通过个体更新量降低个体的待优化的维度数量,充分发挥遗传算法的寻优能力。仿真结果表明,所提出的方法能够在等功率的子载波分配阶段即可实现所要求的公平度阈值并能最大化系统和速率,证明了所提出方法的有效性。The existing OFDMA resource allocation algorithms cannot effectively maximize the system sum data rate on the premise of guaranteeing the fairness threshold.Aiming at the problem,this paper proposes an OFDMA resource allocation algorithm based on a hybrid genetic algorithm.First,the individuals of the population were divided into different groups and different renewal quantities were set for each group.Then,a greedy sub-carrier allocation method was utilized to initialize the individuals of the population,and renewal quantities of individuals were used to reduce the individual dimensionality to be optimized,thereby giving a full play of the optimization ability of the genetic algorithm.The simulation results show that the proposed method can achieve the required fairness threshold and maximize the sum data rate of the system just in the sub-carrier allocation phase with equal power,which proves the validity of the proposed method.

关 键 词：遗传算法 个体更新量 子载波分配 公平度阈值 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]