论文标题
毫米波MIMO系统的混合预编码：矩阵分解方法
Hybrid Precoding For Millimeter Wave MIMO Systems: A Matrix Factorization Approach
论文作者
论文摘要
本文研究了带有有限的阿尔如图输入的毫米波（MMWAVE）多输入多输出（MIMO）系统的混合预编码设计。预编码问题是对模拟和数字编码器的联合优化，我们将其视为功率和恒定模量约束的矩阵分解问题。我们的工作提出了三个主要贡献：首先，我们提出了充分的条件和混合预言方案的必要条件，即当数据流数量满足NS = minfrank（H）; NRFG时，可以准确地实现无约束的最佳预编码，其中H代表通道矩阵和NRF，而NRF是电台频率的数量（RF）链的数量。其次，我们表明我们的矩阵分级问题中的耦合功率约束可以消除而不会丧失最佳性。第三，我们提出了一个基于Broyden-Fletcher-Goldfarb-Shanno（BFGS）的算法，以使用梯度和Hessian信息来解决我们的矩阵分解问题。提供了几种数值结果，以表明我们提出的算法的表现优于现有的混合预编码算法。
This paper investigates the hybrid precoding design for millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems with finite-alphabet inputs. The precoding problem is a joint optimization of analog and digital precoders, and we treat it as a matrix factorization problem with power and constant modulus constraints. Our work presents three main contributions: First, we present a sufficient condition and a necessary condition for hybrid precoding schemes to realize unconstrained optimal precoders exactly when the number of data streams Ns satisfies Ns = minfrank(H);Nrfg, where H represents the channel matrix and Nrf is the number of radio frequency (RF) chains. Second, we show that the coupled power constraint in our matrix factorization problem can be removed without loss of optimality. Third, we propose a Broyden-Fletcher-Goldfarb-Shanno (BFGS)-based algorithm to solve our matrix factorization problem using gradient and Hessian information. Several numerical results are provided to show that our proposed algorithm outperforms existing hybrid precoding algorithms.
