Hyper-power zero forcing detector for massive MIMO systems

Abstract

In massive multiple-input multiple-output (MIMO) systems when the number of base station antennas is much higher than the number of users, linear detectors, such as zero forcing (ZF) and minimum mean-square error (MMSE), are able to achieve the near-optimal performance due to the favorable massive MIMO channel propagation. But, these detectors employ, in general, exact matrix inversion which is computationally complex for such systems. In this paper, we affirm that computing the exact matrix inversion by direct methods is not necessary to find ZF or MMSE solution. An iterative matrix inversion procedure would yield similar performance. Thus, an efficient iterative matrix inversion based on the hyper-power (HP) method is proposed for massive MIMO detection. The computing efficiency of the iterative matrix inversion is further improved by optimizing the number of terms from the infinite series used in the HP method. Analytical results show that the optimum choice for the number of terms is three from the HP method. Simulation results show that the HP method with the optimum number of terms achieves the near-optimal ZF performance in a small number of iterations. Finally, the Coppersmith–Winograd algorithm for matrix multiplication is employed in order to reduce the computational complexity from $O(K^{3})$ to $O(K^{2.373})$, where K represents the number of users.