Convergence-enhanced 1-bit DACs precoding for massive MIMO-OFDM systems via Anderson acceleration

In the downlink of massive multiple-input multiple-output (MIMO) systems, high-resolution digital-to-analog converters (DACs) are a major source of power consumption. This paper mainly focuses on the precoding design for the downlink of massive MIMO-orthogonal frequency division multiplexing (OFDM) systems employing 1-bit DACs to reduce power consumption. We propose a Douglas-Rachford splitting (DRS)-based 1-bit precoding algorithm, where operator linearization is adopted during iterations to avoid matrix inversion, thereby reducing computational complexity. To enhance convergence efficiency, we demonstrate that the proposed precoding algorithm is a fixed-point iteration and introduce an Anderson acceleration module, developing an Anderson acceleration linearized DRS (LDRS-AA) precoding algorithm. Notably, we introduce a decision function to improve the stability of classical Anderson acceleration. A detailed analysis of the convergence and computational complexity for the proposed algorithms is also provided. Simulation results show that the proposed Anderson acceleration scheme achieves significant convergence speed improvement without performance loss. In addition, the proposed precoding algorithm achieves superior bit error rate (BER) performance, exhibiting approximately 1.25 dB and 1 dB performance gains over existing advanced algorithms under quadrature phase shift keying (QPSK) modulation and 16-ary quadrature amplitude modulation (QAM), respectively.