Efficient base station deployment in specialized regions with splitting particle swarm optimization algorithm

Abstract

Signal coverage quality and intensity distribution in complex environments pose a critical challenge, particularly evident in high-density personnel areas and specialized regions with intricate geographic features. This challenge leads to the inadequacy of the traditional two-dimensional base station model under the strain of communication congestion. Addressing the intricacies of the scenario, this paper focuses on the conditionally constrained deployment of base stations in special areas. It introduces a Splitting Particle Swarm Optimization (SPSO) algorithm, enhancing the algorithm’s global optimization capabilities by incorporating the concepts of splitting and parameter adjustments. This refinement aims to meet the communication requirements of customers in complex scenarios. To better align with the real-world communication needs of base stations, simulation experiments are conducted. These experiments involve assigning fixed coordinates to the special region or randomly generating its position. In the conducted experiments, the SPSO achieves maximum coverage rates of 99.24% and 99.00% with fewer target points and 93.56% and 96.16% with more target points. These results validate the optimization capability of the SPSO algorithm, demonstrating its feasibility and effectiveness. Ablation experiments and comparisons with other algorithms further illustrate the advantages of SPSO.