Cellular Network Planning via Local Regularity Optimization

We propose a cell planning method for wireless cellular networks to simultaneously balance the volume shares of the cells and to preserve their regularity. In this framework, we first optimize the base station locations to minimize the coefficient of variation (CoV)-based service demand share metric using the power Voronoi algorithm. Then, we maximize the downlink coverage probability by defining a local regularity optimization problem and solve it through particle swarm, farthest point, average point, and spatial median optimization methods. Finally, we apply the proposed methods on a real network to show how the proposed methods simultaneously minimize both CoV-based service demand share and local regularity metrics.