空天预警研究学报2025，Vol.39Issue(6)：419-424,6.DOI:10.3969/j.issn.2097-180X.2025.06.006
面向5G的基于深度确定性策略梯度的资源分配算法
Resource allocation algorithm based on deep deterministic policy gradient for 5G communication
摘要
Abstract
In order to address the dynamic scheduling issue of communication and computing resources caused by the characteristic differences of service scenarios such as ultra-reliable low-latency communication(URLLC)and massive machine type communication(mMTC),a resource allocation algorithm based on deep de-terministic policy gradient(DDPG-RA)is proposed.Firstly,an optimization model aimed at minimizing the total system delay and energy consumption is constructed.Then,the DDPG framework is used to design the multi-di-mensional state space and continuous action decision-making mechanism.Finally,differentiated reward functions are designed respectively for the delay-sensitive URLLC and the energy-sensitive mMTC to achieve the dynamic optimization allocation of resources.The simulation results show that in typical urban scenarios,compared with the traditional deep Q network(DQN)algorithm and the Function as a Service(FAAS)algorithm,the DDPG-RA algorithm reduces the task processing delay of URLLC users by 4.3%,and that in the high-load scenario where the number of user devices are increased to 14,the energy consumption of the DDPG-RA algorithm is 17.6%low-er than that of FAAS algorithm.关键词
5G通信/边缘计算/深度确定性策略梯度/资源分配/超可靠低时延通信/海量机器类通信Key words
5G communication/edge computing/deep deterministic policy gradient(DDPG)/resource allo-cation/ultra-reliable low-latency communication(URLLC)/massive machine type communication(mMTC)分类
信息技术与安全科学引用本文复制引用
吴名星..面向5G的基于深度确定性策略梯度的资源分配算法[J].空天预警研究学报,2025,39(6):419-424,6.基金项目
长沙民政职业技术学院教授科研项目(2023JB15) （2023JB15）
