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Using Clustering Techniques to Plan Indoor Femtocell Base Stations Layout in Multi-floors

机译:使用聚类技术计划在多层楼层中的室内毫微微小区基站布局

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摘要

Long-term evolution LTE' advanced-based heterogeneous networks are used to improve spectral efficiency per unit area. Nowadays, the network specialists try to increase the capacity of indoor by adding indoor base stations, but other problems appear to them because they are adding them without considering critical constraints such as the number of users, type of base stations, and type of wall, indoor and outdoor interference. This paper proposed a system using cluster techniques to facilitate the process of cell planning that involves locating and configuring infrastructure for mobile networks. The density-based spatial clustering of applications with noise (DBSCAN) algorithm was modified to solve the problem of coverage indoor area, with the existence of obstacles to choose suitable femtocell stations which satisfy minimum path loss and maximize coverage area and minimize cost with guaranteed path loss threshold. Subsequently, Hierarchical Agglomerative Clustering (HAC) was modified to maximize Signal to Interference plus Noise Ratio SINR. Suitable penetrations of 4 and 5 G are used and different types of obstacles taking into consideration their penetration values. The results of this algorithm indicate that the proposed algorithm conducts to decrease the number of Femtocells so minimize the cost and maximize SINR with a grantee pass loss threshold.
机译:长期演进LTE的基于先进的异构网络用于改善每单位面积的光谱效率。如今,网络专家试图通过添加室内基站提高室内的容量,但其他问题出现了它们,因为他们在不考虑的关键限制,如用户数,基站的类型和墙壁类型,室内和室外干扰。本文提出了一种使用群集技术的系统,以便于涉及用于定位和配置移动网络的基础架构的小区规划的过程。修改了具有噪声(DBSCAN)算法的应用的基于密度的空间聚类,以解决覆盖室内区域的问题,存在障碍物来选择合适的毫微微蜂窝站,这些毫微微小区站满足最小路径损耗并最大限度地提高覆盖区域并最大限度地减少了保证路径的成本损失阈值。随后,修改了分层附聚类聚类(HAC)以使信号最大化到干扰加噪声比SINR。考虑到它们的渗透值,使用了4和5g的合适渗透和不同类型的障碍物。该算法的结果表明,所提出的算法对减少毫微微粒细胞的数量,从而最小化成本并最大化具有授予者损耗阈值的SINR。

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