Optimization of 5G base station deployment based on quantum genetic algorithm in outdoor 3D map

Abstract

To solve the problems of unreasonable deployment and high construction costs caused by the rapid increase of the fifth generation (5 G) base stations, this article proposes a 5 G base station deployment optimization method that considers coverage and cost weights for certain areas in Kowloon, Hong Kong. Initially, we utilize three-dimensional (3D) maps and ray-tracing models to simulate signal propagation, incorporating population density data to distribute users across the street of the map randomly. We select suitable candidate locations for building base stations on the ground and rooftop, and set restrictions on the height of base station towers. The use of existing base station locations is considered to reduce construction costs. Moreover, we propose a dynamically adjusted quantum genetic algorithm (DAQGA) to optimize base station layout, with coverage and construction cost as objective functions. A signal reception strength metric is introduced to evaluate the effectiveness of the optimal layout. Simulation results demonstrate that this optimization method effectively identifies coverage blind spots within the planning area and reveals connectivity issues caused by building obstructions or areas beyond coverage. This method achieves an optimal balance in base station deployment when coverage and cost weights are set at 0.7 and 0.3, respectively. Compared to four other algorithms, the proposed improved algorithm shows significant advantages in convergence speed and stability.