论文标题
重新思考WMMSE：其复杂性可以与BS天线的数量线性尺度？
Rethinking WMMSE: Can Its Complexity Scale Linearly With the Number of BS Antennas?
论文作者
论文摘要
用于最大化加权总数（WSR）的预编码设计是大规模多用户多输入多输出（MU-MIMO）系统下行链路的基本问题。众所周知，由于存在多用户干扰，因此这个问题通常是NP-HARD。加权最小均时误差（WMMSE）算法是WSR最大化的流行方法。但是，其计算复杂性在基站（BS）天线的数量中是立方体，当BS配备大型天线阵列时，这是无法承受的。在本文中，我们考虑了与总和约束（SPC）或Per-Antenna功率约束（PAPC）的WSR最大化问题。对于前者，我们证明任何非平凡的固定点必须具有低维的子空间结构，然后通过利用溶液结构来提出具有线性复杂性的还原WMMSE（R-WMMSE）。对于后者，我们通过使用算法的新型递归设计，提出了一种名为papc-wmmse的线性复杂性WMMSE方法。 R-WMMSE和PAPC-WMMSE都具有简单的封闭形式更新，并保证了固定点的收敛。仿真结果验证了所提出的设计的功效，尤其是与大型MU-MIMO系统的最新方法相比，复杂性要低得多。
Precoding design for maximizing weighted sum-rate (WSR) is a fundamental problem for downlink of massive multi-user multiple-input multiple-output (MU-MIMO) systems. It is well-known that this problem is generally NP-hard due to the presence of multi-user interference. The weighted minimum mean-square error (WMMSE) algorithm is a popular approach for WSR maximization. However, its computational complexity is cubic in the number of base station (BS) antennas, which is unaffordable when the BS is equipped with a large antenna array. In this paper, we consider the WSR maximization problem with either a sum-power constraint (SPC) or per-antenna power constraints (PAPCs). For the former, we prove that any nontrivial stationary point must have a low-dimensional subspace structure, and then propose a reduced-WMMSE (R-WMMSE) with linear complexity by exploiting the solution structure. For the latter, we propose a linear-complexity WMMSE approach, named PAPC-WMMSE, by using a novel recursive design of the algorithm. Both R-WMMSE and PAPC-WMMSE have simple closed-form updates and guaranteed convergence to stationary points. Simulation results verify the efficacy of the proposed designs, especially the much lower complexity as compared to the state-of-the-art approaches for massive MU-MIMO systems.
