检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:王腾[1] 侯丽丽 WANG Teng;HOU Li-Li(Qingdao Institute of Software&College of Computer Science and Technology,China University of Petroleum,Qingdao 266580,China)
机构地区:[1]中国石油大学(华东)青岛软件学院、计算机科学与技术学院,青岛266580
出 处:《计算机系统应用》2024年第4期271-278,共8页Computer Systems & Applications
摘 要:移动边缘计算和超密集网络技术在扩大移动设备计算能力和增加网络容量方面有明显的优势.然而,在两者融合的场景下,如何有效降低基站之间的同信道干扰,减少任务传输的时延和能耗是一个重要研究课题.本文设计了一个基于多基站博弈均衡的分布式无线资源管理算法.将小基站之间的无线资源管理问题转化为博弈问题,提出一种基于奖励驱动的策略选择算法.基站通过迭代不断更新其策略的选择概率,最终优化子信道分配和发射功率的调控.仿真结果表明,我们的算法在提高信道利用率和降低任务处理的时延和能耗方面具有优势.Mobile edge computing and ultra-dense network technologies have obvious advantages in improving the computing power of mobile devices and enhancing network capacity.However,under the scenario of convergence between the two,how to effectively reduce the co-channel interference among base stations and reduce the delay and energy consumption of task transmission is an important research topic.Therefore,this study designs a distributed wireless resource management algorithm based on multi-base station game equilibrium.The wireless resource management problem among small base stations is transformed into a game one to propose a reward-driven strategy selection algorithm.The base stations continuously update the selection probability of their strategies by iterations,which finally optimizes the sub-channel allocation and transmission power regulation.Simulation results show that the proposed algorithm has advantages in improving channel utilization and reducing latency and energy consumption for task transmission.
关 键 词:超密集网络 子信道分配 发射功率调控 博弈论 奖励驱动
分 类 号:TN929.5[电子电信—通信与信息系统]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:3.22.70.233