To reduce the complexity of Massive multiple-input multiple-output (MIMO) signal detection, the iterative method is used for signal detection. Based on the implementation of the iterative method with matrix decomposition, the successive over relaxation algorithm is introduced and the range of relaxation factor is deduced by determinant calculation. Simultaneously, a three-dimensional spatially correlated channel model is built based on two-dimension with geometric method and the analytic form solution of spatially correlated channel is introduced by neglecting the high order. The simulation results show the three-dimensional spatially correlated channel model aggravates channel correlation and decreases detection performance. Under 8 times iteration and certain bit error rate, the signal-to-noise ratio of successive over relaxation iteration decreases with the optimal relaxation factor. In a definite signal-to-noise ratio, bit error rate decreases approximate two orders of magnitude, diversity gain promotes and detection algorithm performs equally 16 times iteration, which can also decrease computational complexity. The successive over relaxation detection algorithm can perform better in less iteration and achieve better detection performance with optimal relaxation factor by considering the signal-to-noise ratio and the complexity.