Research on Wireless Channel Modeling Based on Clustering Algorithm

In recent years, the cluster based channel modeling method has been widely used. Excellent clustering algorithm can improve the accuracy of channel mode. In this paper, firstly, in view of the shortcomings of the existing K-Power-Means algorithm, two methods are used for better clustering performance. The metric of peak value of relative density effectively enhance the stability. Besides, the method of maximum and minimum distance is used to determine the cluster center. Angle weight value is calculated based on the average distance, which improves the clustering performance. Secondly, a novel clustering algorithm, based on minimum spanning tree, is proposed to improve clustering performance in specific cases. The performance of this algorithm is compared with that of the other two algorithms in terms of multipath components clustering, and the influences of artificial parameters on the clustering performance are explored.