Hybrid Stochastic Algorithms for Optimal Line-of-Sight Site Configuration of 5G Base Station in HetNet

5G cellular networks are susceptible to outdoor obstacles so they require better and stronger BS implementation optimization to maximize service coverage. However, the current BS location planning techniques are not optimal because they do not consider Line-of-Sight (LOS) and Downlink methods. In this work, a reliable BS site configuration framework is proposed to maximize service coverage and overcome cost challenges in urban outdoor 5G deployment. This framework jointly optimizes three key 5G network practical deployment aspects to achieve optimal 5G deployment in urban outdoor areas. First, two-dimensional spatial analysis models the heterogeneous network incorporating line-of-sight coverage, Massive MIMO transmission configurations, and precise channel estimation. This analysis, powered by a robust hybrid GIS-based stochastic algorithm, pinpoints the ideal base station locations that maximize service coverage within the chosen network configuration. Finally, an optimal power allocation strategy with precoding scheme MR and RZF efficiently allocates resources within the Massive MIMO architecture, ensuring a robust and cost-effective 5G network with maximized coverage. Comprehensive simulations demonstrate the proposed model outperforms recent studies for 5G network planning, enabling streamlined costs, reduced energy consumption, and maximized service coverage in heterogeneous networks.