Silhouette Analysis Based K-Means Clustering in 5G Heterogenous Network

To meet the increasing traffic demand in the telecom industry, Heterogeneous concepts are employed in 5G. A femtocell is a kind of small cell that transmits less power than a macrocell. Hence, the range of coverage offered by these cells is lesser compared to macrocells. The frequency reuse concept is employed due to resource constraints. The purpose of this present research is to investigate the effectiveness of this concept through clustering. The K-means algorithm is used for clustering. A silhouette analysis is performed to determine the effectiveness of clustering. Python version 3.10.6 is used for simulation. From the analysis, it is inferred that the silhouette score is significant only for sparse network environments when compared to dense network environments.