Low-complexity linear precoding for downlink large-scale MIMO systems

In this work, we present a low-complexity linear precoding scheme for downlink large-scale multiple-input multiple-output (MIMO) systems. The proposed scheme can achieve near minimum mean square error (MMSE) precoding performance in terms of the sum rate and is based on a matrix polynomial instead of matrix inversion. Simulation results show that matrix polynomials consisting of only a few terms are sufficient to closely approach the sum rate of the classical MMSE precoder and to perform orders of magnitude better than the simple conjugate beamforming (BF) precoder. We derive exact expressions for the computational complexity of the proposed scheme in terms of the number of additions and multiplications and compare it to the complexity of the BF and MMSE precoders. Our complexity analysis shows that for large number of base station antennas N compared to the number of generated transmit symbols τ per channel estimate and large number of users K, the proposed polynomial precoder has a lower complexity than the classical MMSE precoder.