基于SAOR的Massive MIMO系统信号检测算法

大规模多输入多输出(Massive multiple input multiple output, Massive MIMO)系统采用最小均方误差(Minimum mean square error, MMSE)接收检测方法时存在矩阵求逆复杂度高的问题,已有较多降低复杂度的研究。在降低检测算法复杂度的同时,如何提高算法收敛速度和检测性能一直是人们关注的焦点。本文将对称加速超松弛(Symmetric accelerated over-relaxation, SAOR)迭代算法应用于Massive MIMO系统信号检测中,避免了复杂的矩阵求逆计算,实现了复杂度较最小均方误差算法降低了一个数量级。仿真结果表明,基于SAOR的检测方法通过较少的迭代次数就能逼近最小均方误差（Minimum mean square error, MMSE）算法的检测性能,为Massive MIMO系统中接收信号的快速检测提供了较好的实现方法。

SAOR-Based Signal Detection Algorithm for Massive MIMO System

The minimum mean square error (MMSE) detection method in the massive multiple input multiple output (MIMO) system has a problem that the matrix inversion complexity is too high. In recent years, there have been many studies to reduce the complexity. How to improve the convergence speed and detection performance of the algorithm while reducing the complexity of the detection algorithm has always been the focus of attention. The symmetric accelerated over-relaxation (SAOR) iterative algorithm is applied to the signal detection of massive MIMO systems, which avoids complicated matrix inversion calculation, and the implementation complexity is reduced by an order of magnitude compared with the MMSE method. The simulation results show that the SAOR-based detection method can approach the detection performance of the MMSE algorithm with fewer iterations, which provides a better implementation method for the fast detection of received signals in massive MIMO systems.