In this paper, we consider the one-bit precoding problem for the multiuser downlink massive multiple-input multiple-output (MIMO) system with phase shift keying (PSK) modulation and focus on the celebrated constructive interference (CI)-based problem formulation. We first establish the NP-hardness of the problem (even in the single-user case), which reveals the intrinsic difficulty of globally solving the problem. Then, we propose a novel negative $\ell_1$ penalty model for the considered problem, which penalizes the one-bit constraint into the objective with a negative $\ell_1$-norm term, and show the equivalence between (global and local) solutions of the original problem and the penalty problem when the penalty parameter is sufficiently large. We further transform the penalty model into an equivalent min-max problem and propose an efficient alternating optimization (AO) algorithm for solving it. The AO algorithm enjoys low per-iteration complexity and is guaranteed to converge to the stationary point of the min-max problem. To further reduce the computational cost, we also propose a low-complexity implementation of the AO algorithm, where the values of the variables will be fixed in later iterations once they satisfy the one-bit constraint. Numerical results show that, compared against the state-of-the-art CI-based algorithms, both of the proposed algorithms generally achieve better bit-error-rate (BER) performance with lower computational cost, especially when the problem is difficult (e.g., high-order modulations, large number of antennas, or high user-antenna ratio).
翻译:在本文中,我们考虑了多用户下行连接大规模多投入多输出(MSIMO)系统的单位预码问题,即:通过逐步转换键盘(PSK)调节,对多投入多输出(MIMO)系统进行一次性的分解,并侧重于已知的建设性干扰(CI)问题配方。我们首先将这一问题的NP-硬性(即使在单一用户案例中),这揭示了全球解决问题的内在困难。然后,我们为所考虑的问题提出了一个全新的负数 $\ ell_ 1美元 的罚款模式,它惩罚了目标中的一位数限制,以负值为负数,1美元-诺尔时,并显示(全球和当地)最初问题的解决方案和刑罚问题之间的等值。我们首先将刑罚模式进一步转换成一个等量的微量问题,并提议一个高效的交替优化(AO)算法来解决这个问题。AO算法的每通量性复杂度较低,并且保证与基于最小值的固定值的计算成本,我们还提议一个更低的运算法,通常将比重的计算结果与一个固定值相比,一个固定值的计算结果将比重。