Research on Rural 5G Base Station Deployment Based on a Hybrid Potential Field-PSO Algorithm

In light of the rapid advancements in 5G technology and the concomitant proliferation of base stations, the deployment of these networks in rural areas is encumbered by various challenges, including coverage efficiency, signal interference, and substantial financial expenditures. To address these challenges, this paper puts forth an innovative hybrid algorithm that integrates potential field and particle swarm optimization to address the multi-objective planning problem. The proposed algorithm incorporates a dynamically adjustable potential field mechanism that utilizes gravitational and repulsive potentials to guide the particle search, thereby effectively circumventing the convergence on local optima and enhancing the global optimization capacity. The simulation results demonstrate that the enhanced algorithm attains superior base station layouts with augmented coverage performance and computational efficiency, surpassing the capabilities of existing algorithms. The objective of this study is to furnish relatively straightforward and efficient 5G deployment strategies for rural and complex terrain, thereby addressing the necessity for high-speed and reliable networks. This endeavor aims to foster the development of digital rural areas and contribute to the revitalization of rural regions.