聂益芳,MBUGUA Allan Wainaina,李余,等. 无线信道建模中二分K均值聚类多径分簇算法[J]. 电波科学学报,2023,38(2):284-291. DOI: 10.12265/j.cjors.2022021
      引用本文: 聂益芳,MBUGUA Allan Wainaina,李余,等. 无线信道建模中二分K均值聚类多径分簇算法[J]. 电波科学学报,2023,38(2):284-291. DOI: 10.12265/j.cjors.2022021
      NIE Y F, MBUGUA A W, LI Y, et al. Multi-path clustering method based on bisecting K-means clustering in wireless channel modeling[J]. Chinese journal of radio science,2023,38(2):284-291. (in Chinese). DOI: 10.12265/j.cjors.2022021
      Citation: NIE Y F, MBUGUA A W, LI Y, et al. Multi-path clustering method based on bisecting K-means clustering in wireless channel modeling[J]. Chinese journal of radio science,2023,38(2):284-291. (in Chinese). DOI: 10.12265/j.cjors.2022021

      无线信道建模中二分K均值聚类多径分簇算法

      Multi-path clustering method based on bisecting K-means clustering in wireless channel modeling

      • 摘要: 为了对无线信道中的多径分量进行合理分簇,提出了一种毫米波信道二分K均值聚类多径分簇方法,解决了传统的K均值聚类分簇方法只能实现局部最优分簇的问题. 采用马氏距离(Mahalanobis distance, MD)衡量多径分量距离(multi-path component distance, MCD),以簇分裂和迭代计算的方式对多径进行分簇. 采用毫米波室内信道实验测试数据,验证了所提算法的有效性和可行性. 结果表明,所提算法比传统K均值聚类分簇方法获得的分簇结果更合理,能将信道中多径参数相似度较高的多径有效且唯一地分配到同一簇.

         

        Abstract: In order to rationally allocate multi-path component (MPC) of wireless channels to different clusters, a multi-path clustering algorithm based on Bisecting K-means clustering was proposed for millimeter-wave channels to solve the problem of partial optimization of traditional K-means clustering methods. The MPC clustering was implemented based on the cluster split and iteration computation strategy, when the Mahalanobis distance (MD) was regarded as the multipath component distance (MCD). The experiment measurement in indoor millimeter-wave channel was conducted to verify the effectiveness and feasibility of the proposed method. The experimental results show that the clustering result of proposed method is more rational than those of traditional K-means clustering methods, and the highly correlated MPCs are reasonably and uniquely allocated to the same cluster.

         

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