Beamforming with Hybrid Channel Information in Spatially Correlated MISO Channels

In this paper, we propose a new beamforming scheme that utilizes both long-term and instantaneous channel state information (CSI). First, the dimension of the channel is effectively reduced by considering dominant eigen-dimensions of the channel covariance matrix. Then, the beam weight is generated using the instantaneous CSI of the effectively dimension-reduced channel. The reduction of the channel dimension is determined to maximize the signal-to-noise ratio (SNR) in an average sense considering the amount of feedback signaling burden and spatial correlation of the channel. It is analytically shown and verified by computer simulation that the proposed scheme outperforms conventional beamforming schemes when the same amount of feedback signaling burden is utilized.