一种优化云无线接入网络资源分配算法  

An Optimization Cloud Radio Access Network Resource Allocation Algorithm

作　　者：付国帅 FU Guoshuai(Zhengzhou University of Industrial Technology,Zhengzhou 451150,China)

机构地区：[1]郑州工业应用技术学院,郑州451150

出　　处：《火力与指挥控制》2023年第11期67-71,80,共6页Fire Control & Command Control

基　　金：河南省科技厅科技攻关计划基金(182102310961);郑州市智能交通视频图像感知与识别重点实验室项目([2020]34)。

摘　　要：在云接入网络(cloud radio access network,C-RAN)中,设备至设备(device-to-device,D2D)通信共享蜂窝用户的资源,提高了频谱利用率。但是资源共享也引入干扰问题,降低了网络的和速率。提出基于教学优化法的资源分配算法(teacher learner based optimization-resource allocation,TLRA)。TLRA算法在分配资源时,考虑了干扰问题,并以蜂窝用户端的干扰不高于预定阈值为约束条件,建立目标问题。利用教学优化法求解目标问题,获取最优的资源分配策略。性能分析表明,提出的TLRA算法提高了系统和速率,Jain公平指数接近0.8。In cloud radio access network(C-RAN),the sharing of cellular user's resource by multiple D2D communications improves the spectral efficiency,which ultimately degrades the sum rate of the network by interference problems introduced to resources sharing.Therefore,Teacher Learner based Optimization-Resource Allocation(TLRA)algorithm is proposed.In TLRA,the interference problem is considered,the objective problem is established,and the constrain condition is that the interference of cellular user terminal is less than the predetermined threshold.The teacher learner algorithm is used to solve the objective problem,and the optimal resource allocation policy is obtained.The performance analysis demonstrate that the proposed TLRA algorithm improves the sum rate of the system,the fairness index is approaching 0.8.

关 键 词：云无线接入网络 D2D通信 资源分配 教学优化算法 和速率 

分 类 号：TN915[电子电信—通信与信息系统]