A Virtual Small Cell Formation-Based Load-Balancing in Ultra-Dense Cellular Network

Abstract

With the emergence of 5G networks, the demand for high-speed data transfer has increased significantly. However, the conventional cellular network architecture may not be sufficient to support the increasing number of connected devices and their data demands. To address this issue, the concept of virtual small cells proposed as a solution. Virtual small cells are software-defined and can be deployed flexibly to offload traffic from congested areas and balance the load across the network. Due to the uneven distribution of users, conventional small cells and macro cells can become overloaded. Therefore, load balancing is critical to ensure network performance and handle the increasing data traffic. We propose a load-balancing approach based on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. The algorithm groups users based on their proximity and hands over the users to on-demand virtual small cells. We evaluate the proposed approach using simulations that consider various scenarios, including varying numbers of users, varying levels of network congestion, and different configurations of virtual small cells. The results show that the proposed approach effectively balances the load among cells, resulting in better network performance, particularly in congested areas.