Channel List Selection Based on Quality Prediction in WirelessHART Networks

查看全文 作　　者：Gongpu [1]Chen;Rui [1]Ma;Mengdan [1]Lei;Xianghui [1]Cao

机构地区：[1]Southeast University,Nanjing 210096,China

出　　处：《Journal of Communications and Information Networks》索引2018年第3卷第3期,共8页

基　　金：This work was supported in part by the National Natural Science Foundation of China(No.61573103);the State Key Laboratory of Synthetical Automation for Process Industries,and the Fundamental Research Funds for the Central Universities.The associate editor coordinating the review of this paper and approving it for publication was X.Cheng. 摘　　要：WirelessHART is one of the most widely used technologies in industrial wireless networks.However,its performance is highly influenced by the quality of wireless channels.To improve the reliability of wireless communications,WirelessHART employs channel blacklisting and channel hopping mechanisms,which highlights the importance of channel assessment.Traditional methods generally resort to packet reception ratio(PRR)of the previous time slot to assess and allocate channels,but this is not accurate.In this paper,we propose a learning-based framework for predicting the PRR,and on the basis of the predicted PRR,we develop a heuristic channel selection algorithm to confirm the channel list,which takes into account the balance of channel diversity and route diversity.Simulation results demonstrate that our algorithm outperforms existing ones in terms of achieved reliability. 关键词：WIRELESSHART channel quality deep learning PREDICTION channel selection

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Channel List Selection Based on Quality Prediction in WirelessHART Networks

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