一种基于聚类算法的载波分配方法  

A carrier allocation method based on clustering algorithm

作　　者：徐东辉 刘江亮 刘思佚 刘丁胤 XU Donghui;LIU Jiangliang;LIU Siyi;LIU Dingyin(Rocket Force University of Engineering,Xi’an 710025,China)

机构地区：[1]火箭军工程大学,西安710025

出　　处：《兵器装备工程学报》2024年第11期253-258,共6页Journal of Ordnance Equipment Engineering

摘　　要：5G超密集组网技术(ultra-dense networks,UDN)是解决5G网络流量快速增长的关键技术,但是在UDN网络中基站的致密性会导致站间同频干扰、邻道干扰增加、频谱资源管理难度大等问题。针对UDN网络中干扰和频谱资源管理难度大的问题进行研究,提出基于k-means聚类算法对微基站进行聚类处理的思路,即将多个微基站分为不同的基站簇进行统一管理和调配,基于基站簇之间的位置将不同的频谱资源分配给基站簇,再将频谱资源中的正交载波分配给簇内的基站,实现对位置相近的基站进行频率上的分离,有效降低了基站之间的干扰,降低了频谱资源分配给用户的计算难度。仿真结果表明:基于k-means聚类算法对微基站进行聚类处理能够有效降低站间同频干扰和邻道干扰的影响,同时也能够降低频谱资源分配给用户时的计算难度。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.

关 键 词：超密集组网 K-MEANS聚类 同频干扰 频率管理 微小基站 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]