The task of signal detection is to estimate the users’ sending signal through the signal received by the base station. For uplink massive multiple-input-multiple-output (MIMO) system, a hybrid iterative detection algorithm called SDGS based on steepest descent (SD) algorithm and Gauss Seidel (GS) iteration is proposed. The algorithm can solve the problem of matrix inverse in minimum mean square error (MMSE) algorithm and reduce the computational complexity from O(K³) to O(K²), where K is the number of users. Meanwhile, the SD algorithm has a good convergence direction, which speeds up convergence in the iteration. In this paper, a further improved method to compute the log likelihood ratio (LLR) is proposed to improve the detection performance while the complexity is kept of at the level of O(K²). Simulation results show that the improved hybrid iterative algorithm can converge rapidly and approach the performance of the MMSE algorithm with only a small number of iterations.