Abstract: |
5G ultra dense networks (UDN) is a key technology to solve the rapid growth of 5G network traffic.However, the density of base stations in UDN networks can lead to inter station co frequency interference, increased adjacent channel interference, and difficulty in spectrum resource management.This article focuses on the issues of interference and difficulty in managing spectrum resources in UDN networks.A clustering approach based on k means clustering algorithm is proposed for micro base stations, which involves dividing multiple micro base stations into different clusters for unified management and allocation.Different spectrum resources are allocated to base station clusters based on their positions, and then orthogonal carriers in the spectrum resources are allocated to base stations within the cluster, realizing frequency separation for nearby base stations, effectively reducing interference between base stations and reducing the computational difficulty of allocating spectrum resources to users.The simulation results show that clustering micro base stations based on k means clustering algorithm can effectively reduce the impact of inter station co frequency interference and adjacent channel interference, and also reduce the computational difficulty of allocating spectrum resources to users. |