In this paper, the number and location of the deployment of indoor small base stations are used as optimization variables to ensure coverage and reduce the interference between base stations as conditions. Based on the corrected model, a differential evolution hybrid particle swarm optimization algorithm is used to solve the optimization objectives. In the process of each iteration, the solution solution given by the optimization algorithm is covered by the prediction model. The signal coverage degree in the target area is calculated and fed back to the particle swarm optimization algorithm as the historical experience data for learning, and the final planning scheme is output, which has certain engineering practice basis and guiding significance for operation and maintenance work.
Changxing LiQing ZhangZhang Long-yao