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作 者:Fei Du Yu Zhang Qingliang Li Xinyue Zhang Bo Zhu Zihao Fu Suiyan Geng Xiongwen Zhao
机构地区:[1]State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,School of Electrical and Electronic Engineering,North China Electric Power University,Beijing 102206,China [2]Hebei Key Laboratory of Power Internet of Things Technology,North China Electric Power University,Baoding 071003,Hebei,China [3]National Key Laboratory of Electromagnetic Environment,China Research Institute of Radiowave Propagation,Qingdao 266107,China
出 处:《China Communications》2022年第11期99-111,共13页中国通信(英文版)
基 金:supported by the National Key Laboratory of Electromagnetic Environment(No.202101004);the National Nature Science of China(NSFC)(No.61931001),respectively。
摘 要:Time-varying channel modeling plays an important role for many applications in time-variant scenarios,while most clustering algorithms focus on static channels and cannot accurately model the channel time-evolution properties.In this paper,a fuzzy clustering algorithm based on multipath component(MPC)trajectory is proposed.Firstly,both the distance and velocity similarities of the MPCs in different snapshots are taken into account to track the MPC trajectory,in which the fuzzy scheme and a kernel function are used to calculate the distance and velocity similarities,respectively.Secondly,a fuzzy MPC trajectory clustering algorithm is proposed to cluster the MPCs in multiple snapshots.The MPCs in a snapshot are clustered according to the membership,which is defined as the probability that a MPC belongs to different clusters.Finally,time-varying channels at 28 GHz are simulated to validate the performance of our proposed algorithm.The results show that our proposed algorithm is able to accurately identify the clusters in time-varying channels compared with the existing clustering algorithms.
关 键 词:channel modeling TIME-VARYING clustering multiple path component MPC trajectory 6G
分 类 号:TN929.5[电子电信—通信与信息系统] TP311.13[电子电信—信息与通信工程]
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