摘要
为更好满足变电站中大规模设备接入和高可靠低时延业务传输需求,提出了一种适用于变电站业务的多频异构无线通信网络接入选择算法。首先构造了一个异构无线网络覆盖下的变电站场景模型,综合考虑变电站业务对于可靠性和有效性的需求。其次为有效提升接收到信息的新鲜程度,以平均信息年龄(AAoI)作为无线网络接入选择的优化目标函数,提出了基于信息年龄的变电站业务接入选择优化问题。最后利用深度Q学习(DQN)方法求解该问题,以获得最佳的接入选择方案。通过对应用实例与试验数据的分析可以看出,所提出的接入选择优化理论和算法,可以降低业务传输时的平均信息年龄,提升数据的新鲜程度。
To meet the need for a ultra-reliable and low-latency service transmission of large-scale equipment access in substations, we propose a multi-frequency heterogeneous wireless communication network access selection algorithm for substation services. Considering the reliability and effectiveness requirements of these services, we firstly construct a substation scenario model under heterogeneous wireless network coverage. Secondly, to effectively improve the freshness of the information received, we utilize the Average Age of Information(AAoI) as the optimization target function of wireless network access selection and propose the optimization problem of substation service access selection based on the age of information. Finally, we implement the Deep Q-Learning(DQN) method to obtain the best access selection scheme. It can be seen from the analysis of the application examples and the test data that the proposed access selection optimization theory and algorithm can reduce the average age of information during service transmission and improve the freshness of data.
作者
韩东升
岳栩彤
Han Dongsheng;Yue Xutong(Department of Electronic and Communication Engineering,North China Electric Power University,Baoding 071003,China;Hebei Province Electric PowerInternet of Things Technology Key Laboratory,North China Electric Power University,Baoding 071003,China)
出处
《电子测量技术》
北大核心
2022年第20期29-36,共8页
Electronic Measurement Technology
基金
国家自然科学基金(61771195)
中央高校基本科研业务费专项资金(2020MS098)
河北省省级科技计划(SZX2020034)项目资助。
关键词
变电站
异构无线网络
接入选择
平均信息年龄
深度Q学习
substation
heterogeneous wireless network
access selection
average age of information
deep Q-learning
