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作 者:韩会梅 余浩 卢为党[1] HAN Huimei;YU Hao;LU Weidang(College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China)
出 处:《小型微型计算机系统》2024年第12期2979-2984,共6页Journal of Chinese Computer Systems
基 金:国家自然科学基金项目(62001419)资助;浙江省自然科学基金项目(LQ21F010012)资助。
摘 要:5G三大应用场景之一的海量机器类通信(massive Machine Type Communication, mMTC)具有数据包小、功耗低、海量连接等特点,其能解决传统移动通信无法很好支持物联网及垂直行业应用的问题.针对mMTC场景下由于接入设备数量巨大造成的网络拥塞问题,本文提出了一种基于深度确定性梯度下降(Deep Deterministic Policy Gradient, DDPG)的接入等级限制(Access Class Barring, ACB)拥塞控制接入方案.在每个接入时隙,用户确定其优先级,基站采用DDPG算法为每个接入优先级设置ACB接入阻拦概率进行拥塞控制.此外,该方案允许多个用户在同一资源块上传输数据信息,基站采用迭代干扰消除(Successive Interference Cancellation, SIC)算法解码用户数据,进而提升成功接入用户数.仿真结果表明,与现有拥塞控制策略相比,所提方案能在满足用户时延需求的同时提升成功接入的用户数.One of the three major application scenarios in 5G,massive Machine Type Communication(mMTC),is characterized by small data packets,low power consumption,and massive connectivity.It tackles the challenges faced by traditional mobile communication in adequately supporting Internet of Things(IoT)and vertical industry applications.To address the network congestion caused by the large number of access devices in the mMTC scenario,an Access Class Barring(ACB)congestion control access scheme based on Deep Deterministic Policy Gradient(DDPG)is proposed in this paper.In each access slot,users determine their priority,and the base station utilizes the DDPG algorithm to set ACB access barring probabilities for each access priority to control congestion.Moreover,this scheme allows multiple users to transmit data information on the same resource block,and the base station employs the Successive Interference Cancellation(SIC)algorithm to decode data of each user iteratively,thereby improving the number of successfully access users.Simulation results demonstrate that the proposed scheme,compared to existing congestion control strategies,enhances the number of successfully accessed users while satisfying user delay requirements.
关 键 词:海量机器类通信 机器间通信 5G 随机接入 接入等级限制 DDPG
分 类 号:TN929[电子电信—通信与信息系统]
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