基于DBSCA聚类算法优化的均值漂移算法的移动通信网络站址规划优化算法研究
Research on Optimization Algorithm for Mo-bile Communication Network Site Planning Based on DBSCA Clustering Algorithm and Optimized Mean Shift Algorithm
摘要: 为适应当今无线通信产业的快速发展,解决基站选址是否合理,本文提出了一种基站定位算法,结合均值漂移算法和DBSCAN聚类算法来解决基站的合理选址问题。该算法将大区域划分为较小的子区域,并利用均值漂移算法计算每个子区域内局部服务体密度的密度极值点。根据每个高密区域的大小,建立覆盖范围不同的基站。采用DBSCAN聚类算法对近距离弱覆盖区域进行聚类,优化传统均值漂移算法的收敛速度。实验结果表明,该算法在寻找基站定位和数据分类的最优解方面具有实用性和有效性。
Abstract:
To adapt to the rapid development of the wireless communication industry and solve the problem of whether a base station location is reasonable, this paper proposes a base station positioning algo-rithm that combines the mean shift algorithm and the DBSCAN clustering algorithm to address the issue of rational base station selection. This algorithm divides a large area into smaller sub- regions and uses the mean shift algorithm to calculate the density extreme points of the local service body density in each sub-region. Based on the size of each high-density area, base stations with different coverage ranges are established. The DBSCAN clustering algorithm is used to cluster the weak cov-erage areas at close range, optimizing the convergence speed of the traditional mean shift algorithm. Experimental results show that this algorithm is practical and effective in finding the optimal solu-tions for base station positioning and data classification.
参考文献
|
[1]
|
黄骅, 江俊. 基于聚类的无线网络基站选址优化算法研究[J]. 现代信息科技, 2018, 2(9): 50-52.
|
|
[2]
|
苏延平. 依赖混合型位置大数据的均值漂移聚类算法[J]. 山西能源学院学报, 2020, 33(2): 97-99.
|
|
[3]
|
张双寒, 王珊, 王特. 基于DBSCAN聚类的毕星团成员星识别方法[J]. 现代信息科技, 2021, 5(24): 146-149.
|
|
[4]
|
张乾, 张强. 动态规划迭代算法在末端防御中的应用[J]. 电子设计工程, 2021, 29(3): 104-107.
|
|
[5]
|
赵华茗, 余丽, 周强. 基于均值漂移算法的文本聚类数目优化研究[J]. 数据分析与知识发现, 2019, 3(9): 27-35.
|
|
[6]
|
陈琦, 贾元华. 基于人工鱼群算法的移动通信网络基站覆盖优化问题[J]. 北京交通大学学报, 2013, 37(6): 99-102.
|