  Minimum mean square error (MMSE) signal detection algorithm is near- optimal
for uplink multi-user large-scale multiple input multiple output (MIMO)
systems, but involves matrix inversion with high complexity. In this letter, we
firstly prove that the MMSE filtering matrix for large- scale MIMO is symmetric
positive definite, based on which we propose a low-complexity near-optimal
signal detection algorithm by exploiting the Richardson method to avoid the
matrix inversion. The complexity can be reduced from O(K3) to O(K2), where K is
the number of users. We also provide the convergence proof of the proposed
algorithm. Simulation results show that the proposed signal detection algorithm
converges fast, and achieves the near-optimal performance of the classical MMSE
algorithm.
