Abstract: Base station location planning is a significant optimization problem in network communication, and there is a great impact on the quality of network communication. Based on the constrained conditions of base station location planning, this paper constructs a base station location planning optimization model with the network coverage as the optimization index. The traditional optimization algorithms have some disadvantages such as slow convergence rate, easy to fall into local optimal, so this paper proposes an improved whale optimization algorithm. Firstly, aiming at improving the algorithm convergence rate, an adaptive changing strategy for convergence factor decreasing with the iteration number nonlinearly is introduced to improve global convergence ability. Then, the variation disturbance which obeys normal distribution is applied in some individuals to avoid premature convergence of the algorithm. The simulation results of the benchmark functions and the test example of base station location planning test problem show that the improved algorithm proposed in this paper can obtain a more ideal optimal solution and has faster convergence rate.

Key words: base station location planning, whale optimization algorithm, convergence factor, cosine decreasing factor, variation disturbance