Low complexity hybrid iterative algorithm based signal detection in massive MIMO system - Shufeng ZHAO; Bin SHEN; Furong YANG (Dianxin kexue)
Among the uplink signal detection algorithms for massive MIMO systems,the minimum mean square error (MMSE) algorithm can achieve the near-optimal linear detection performance.However,conventional MMSE usually involves high complexity due to the required matrix inversion of large-size matrix,which makes it hard to implement in realistic applications.Based on joint steepest descent (SD) algorithm and Gauss-Seidel iteration,a low complexity hybrid iterative detection algorithm was proposed.The SD algorithm was employed to obtain an efficient searching direction for the following Gauss-Seidel to speed up convergence.Meanwhile,an approximated method was also proposed to compute the bit log-likelihood ratio (LLR) for soft channel decoding.Simulation results verify that the proposed algorithm can converge rapidly and achieve its performance quite close to that of the MMSE algorithm with only a small number of iterations.Meanwhile,the complexity is reduced by an order of magnitude,which is kept consistently of O(K 2).