Low-Complexity SSOR-Based Precoding for Massive MIMO Systems
Low-Complexity SSOR-Based Precoding for Massive MIMO Systems
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DOI：
10.1109/lcomm.2016.2525807
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发表时间：
2016-02
期刊：
影响因子：
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通讯作者：
Tian Xie;L. Dai;Xinyu Gao;Xiaoming Dai;Youping Zhao
中科院分区：
文献类型：
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作者：
Tian Xie;L. Dai;Xinyu Gao;Xiaoming Dai;Youping Zhao
随着大量多输入多输出（MIMO）系统中基站（BS）天线数量的增加，线性预编码方案能够实现近乎最佳的性能，因此比非线性预编码技术更具吸引力。然而，常规的线性预编码方案（例如零孔（ZF）预编码）涉及具有较高计算复杂性的大尺寸的矩阵反转，尤其是在大型MIMO系统中。为了降低复杂性，在这封信中，我们提出了一个基于对称连续的弛豫方法（SSOR）方法的低复杂性线性预编码方案。此外，我们提出了一种简单的方法，通过利用大型MIMO系统中渐近正交性的通道特性来近似基于SSOR的预码的最佳松弛参数。我们表明，所提出的基于SSOR的预编码可以将经典ZF预编码的复杂性降低约一个数量级，而不会损失性能，并且在典型褪色通道中最近提出的线性近似近似编码方案也胜过。
With the increase of the number of base station (BS) antennas in massive multiple-input multiple-output (MIMO) systems, linear precoding schemes are able to achieve the near-optimal performance, and thus are more attractive than nonlinear precoding techniques. However, conventional linear precoding schemes such as zero-forcing (ZF) precoding involve the matrix inversion of large size with high computational complexity, especially in massive MIMO systems. To reduce the complexity, in this letter, we propose a low-complexity linear precoding scheme based on the symmetric successive over relaxation (SSOR) method. Moreover, we propose a simple way to approximate the optimal relaxation parameter of the SSOR-based precoding by exploiting the channel property of asymptotical orthogonality in massive MIMO systems. We show that the proposed SSOR-based precoding can reduce the complexity of the classical ZF precoding by about one order of magnitude without performance loss, and it also outperforms the recently proposed linear approximate precoding schemes in typical fading channels.