Emergent Mind

Abstract

We study a downlink multi-user multiple-input single-output (MU-MISO) system in which the base station (BS) has a large number of antennas with cost-effective one-bit digital-to-analog converters (DACs). In this system, we first identify that antenna-selection can yield a non-trivial symbol-error-rate (SER) performance gain by alleviating an error-floor problem. Likewise the previous works on one-bit precoding, finding an optimal transmit-signal vector (encompassing precoding and antenna-selection) requires exhaustive-search due to its combinatorial nature. Motivated by this, we propose a low-complexity two-stage algorithm to directly obtain such transmit-signal vector. In the first stage, we obtain a feasible transmit-signal vector via iterative-hard-thresholding algorithm where the resulting vector ensures that each user's noiseless observation is belong to a desired decision region. In the second stage, a bit-flipping algorithm is employed to refine the feasible vector so that each user's received signal is more robust to additive Gaussian noises. Via simulation results, we demonstrate that the proposed method can yield a more elegant performance-complexity tradeoff than the existing one-bit precoding methods.

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