Abstract
In this paper, we propose a two-step algorithm that can achieve any tradeoff point between antenna selection complexity and performance for a massive multiple-input multiple-output (M-MIMO) system. The first and second steps target low complexity and high performance, respectively, in the antenna selection. For the first-step antenna selection, we propose a correlation-based best-first selection algorithm that selects the least spatially correlated antennas. For the second-step selection, we consider a performance-aware algorithm that maximizes the singular values of a selected channel matrix. By adjusting the number of selected antennas in each step, we can actively balance the complexity and performance of the M-MIMO system. The computational complexity and the bit-error-rate performance of various antenna selection algorithms have been analyzed and compared. The investigation in the paper provides a good reference for further study for an antenna selection-based M-MIMO system.
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