Indoor positioning based on the cellular network has become the preferred carrier-class method.Due to the common infrastructure of the communication network,it has a wide range of coverage and it is without the need for reinvestment of infrastructure,which has become one of hot spots in the field of 5G communication.In the cellular positioning scene of network indoor,the layout of station will directly affect the number of the first acceptance diameter,arriving time TOA (Time of Arrival),measurement error and so on,then it will affect the positioning accuracy.A base station selection optimization algorithm for indoor location was proposed,which reduces the deviation due to the base station layout.Firstly,an indoor three-dimensional positioning model with error suppression is proposed to suppress the inaccuracy of single model localization.TOA information is used to suppress the error caused by the virtual locating point in the TDOA model.Secondly,according to the results of the selection of different base stations,the isolated point are removed by the idea of secondary clustering,position of the positioning point is determined according to the class with the largest number of sample nodes in the clustering result.The experimental results show that the base station selection optimization algorithm reduces the average deviation of indoor positioning by 15.49% compared with other optimization algorithms.