In the era of the fifth generation (5G) communication networks, massive multiple-input multiple-output (MIMO) systems demand even lower computation complexity and power consumption while catching up with good detection performance. In this paper, a low-complexity nonlinear detection algorithm is proposed for massive MIMO systems, which is based on partial tree search and successive interference cancellation (SIC). The proposed scheme allows us to expedite the detection process by coping with the transmit symbols group by group. As compared to vertical-Bell laboratories layered space time (V-BLAST), the major breakthrough of computation reduction lies in the fact that the partial tree search can assist the detection process to avoid the inversion of the detection matrix required in each recursion of the SIC process. Both computational complexity analysis and simulation results show that our proposed algorithm not only significantly reduces computational complexity, but also has better bit error rate (BER) performance.

中文翻译：

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大规模 MIMO 系统的部分树搜索辅助符号检测

在第五代（5G）通信网络时代，大规模多输入多输出（MIMO）系统要求更低的计算复杂度和功耗，同时追赶良好的检测性能。本文针对大规模MIMO系统提出了一种基于部分树搜索和连续干扰消除(SIC)的低复杂度非线性检测算法。所提出的方案允许我们通过逐组处理发射符号来加快检测过程。与垂直贝尔实验室分层时空（V-BLAST）相比，计算量减少的主要突破在于部分树搜索可以帮助检测过程避免每次递归所需的检测矩阵求逆。 SIC 工艺。