Robust BF in large-scale antenna systems with imperfect channel state information

This paper addresses robust beamforming (BF) design for the uplink transmission of wireless networks, where the base station (BS) equipped with a very large number of antennas communicates with multiple users on the same frequency band simultaneously. Based on the assumption that the wireless channels undergo correlated Rayleigh fading, we first formulate an optimization problem to maximize the output signal-to-interference-plus-noise ratio (SINR) of the intended users. Then, by using the fact that channel uncertainty is norm-bounded and imperfect channel state information (CSI) is available at the BS, we transform the optimization problem to a support vector machine (SVM) regression one, and obtain the robust solution for the BF weight vectors by means of quadratic programming (QP) technique or iterative reweighted least squares (IRWLS) procedure. The computational cost of the proposed robust BF scheme depends on the number of channel vector samples rather than that of the antennas, thus it is suitable for the wireless systems with large-scale antennas. Finally, the efficiency and superiority of the proposed new scheme are confirmed through computer simulation.