Abstract
Hybrid beamforming has been a promising low-cost solution for large millimeter wave MIMO systems. In this letter, with regards to the time-varying propagation environments, based on broad learning (BL), we propose an on-line analog beam selection method. Specifically, we exploit the distinguished ability of BL on incremental learning to track the changing tendency of optimal analog beam in an on-line manner. Moreover, to avoid the time-consuming target calculation, by introducing Laplacian eigenmaps into BL, we propose a semi-supervised on-line analog beam selection method where only few on-line transmissions need to calculate the target. Hence, the proposed method can be conducted efficiently. Simulation results show the effectiveness of the proposed method.
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