Adaptive Best-M Feedback Algorithm for MU-MIMO Systems

In this paper, we propose an adaptive Best-M feedback algorithm designed to reduce the feedback burden especially for orthogonal frequency division multiple access (OFDMA) systems with multi-user multiple-input multiple-output (MU-MIMO) precoding. The key idea of the proposed algorithm is to adaptively control the amount of the feedback information under the consideration of both the channel state information (CSI) and the system objective function and thus to ultimately reduce the feedback burden of all users. Various computer simulation results demonstrate that the feedback burden for users is significantly reduced, while the system throughput performance is being maintained as the conventional Best-M algorithm.