Weighted-combining calibration for implicit feedback beamforming on downlink multiuser MIMO systems

This paper proposes a novel calibration scheme for implicit feedback beamforming on downlink (DL) multiuser (MU) multiple-input multiple-output (MIMO) systems. In the proposed scheme, an access point (AP) calculates calibration coefficients from ratios of DL and uplink (UL) channel state information (CSI) corresponding to multiple stations (STAs), and then combines multiple coefficients with minimum mean square error (MMSE) weights. Although it is difficult to calculate MMSE weights since Gaussian noise terms due to estimated CSI error exist in the denominator of the mean square error, we derive the weights using a linear approximation in the highsignal to noise power ratio (SNR) regime. Simulation results reveal that the proposed scheme obtains signal to interference plus noise power ratio (SINR) gain of more than 6.9 dB over a calibration scheme without combining, at 10% cumulative distribution function (CDF) and SNR of 40 dB. It is found that the proposed scheme improves the calibration accuracy considerably.