An Efficient Design of One-Bit DACs Precoding for Massive MU-MIMO Downlink

In massive multi-user multi-input–multi-output (MU-MIMO) downlink transmission systems, the total power consumption of the base station is mainly attributed to high-resolution digital-to-analog converters (DACs). Therefore, utilizing one-bit DACs can effectively reduce the system power consumption. This work investigates the one-bit DACs precoding problem in massive MU-MIMO systems. Typically, the one-bit DACs precoding problem based on the minimum mean square error criterion is an NP-hard problem, making it challenging to solve. By exploiting the structural properties of nonconvex constraints, the nonconvex optimization problem is transformed into an equivalent continuous-domain mathematical programming problem with equilibrium constraints. The projected gradient method is used for obtaining the quantized precoding signals, and the method is optimized by introducing a step-size adjustment coefficient. Simulation results demonstrate that the improved projected gradient method can effectively reduce the uncoded bit error rate and achieve a performance gain of approximately $\text{2}\,\text{dB}$ with 16 quadrature amplitude modulation signaling. The simulations also demonstrate the better robustness of the suggested method with imperfect channel state information. Specifically, we evaluate the power consumption of the proposed algorithm to that of the zero-forcing precoder with different resolution DACs, illustrating its superior power efficiency. Furthermore, we demonstrate the effectiveness of the proposed algorithm through a theoretical analysis of the convergence, complexity, and exact property of the optimal solution.