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.
@article{arxiv.1507.04443,
title = {Low-complexity near-optimal signal detection for uplink large-scale MIMO systems},
author = {Xinyu Gao and Linglong Dai and Yongkui Ma and Zhaocheng Wang},
journal= {arXiv preprint arXiv:1507.04443},
year = {2015}
}