Downlink transmission techniques for multiuser (MU) multiple-input multiple-output (MIMO) systems have been comprehensively studied during the last two decades. The well-known low complexity linear precoding schemes are currently deployed in long-term evolution (LTE) networks. However, these schemes exhibit serious shortcomings in scenarios when users’ channels are strongly correlated. The nonlinear precoding schemes show better performance, but their complexity is prohibitively high for a real-time implementation. Two-stage precoding schemes, proposed in the standardization process for 5G new radio (5G NR), combine these two approaches and present a reasonable trade-off between computational complexity and performance degradation. Before applying the precoding procedure, users should be properly allocated into beamforming subgroups. Yet, the optimal solution for user selection problem requires an exhaustive search which is infeasible in practical scenarios. Suboptimal user grouping approaches have been mostly focused on capacity maximization through greedy user selection. Recently, overlapping user grouping concept was introduced. It ensures that each user is scheduled in at least one beamforming subgroup. To the best of our knowledge, the existing two-stage precoding schemes proposed in literature have not considered overlapping user grouping strategy that solves user selection, ordering, and coverage problem simultaneously. In this paper, we present a two-stage precoding technique for MU-MIMO based on the overlapping user grouping approach and assess its computational complexity and performance in IoT-oriented 5G environment. The proposed solution deploys two-stage precoding in which linear zero forcing (ZF) precoding suppresses interference between the beamforming subgroups and nonlinear Tomlinson-Harashima precoding (THP) mitigates interuser interference within subgroups. The overlapping user grouping approach enables additional capacity improvement, while ZF-THP precoding attains balance between the capacity gains and suffered computational complexity. The proposed algorithm achieves up to 45% higher MU-MIMO system capacity with lower complexity order in comparison with two-stage precoding schemes based on legacy user grouping strategies.

中文翻译：

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面向物联网的5G MU-MIMO系统中基于重叠用户分组方法的两阶段预编码

在过去的二十年中，对多用户（MU）多输入多输出（MIMO）系统的下行链路传输技术进行了全面的研究。当前，在长期演进（LTE）网络中部署了众所周知的低复杂度线性预编码方案。但是，这些方案在用户的频道紧密相关的情况下表现出严重的缺点。非线性预编码方案显示出更好的性能，但对于实时实现而言，其复杂度高得令人望而却步。在5G新无线电（5G NR）的标准化过程中提出的两阶段预编码方案结合了这两种方法，并在计算复杂度和性能下降之间提出了合理的折衷方案。在应用预编码过程之前，应将用户正确分配到波束成形子组中。然而，用户选择问题的最佳解决方案需要详尽的搜索，这在实际情况下是不可行的。次优的用户分组方法主要集中在通过贪婪的用户选择来实现容量最大化。最近，引入了重叠的用户分组概念。它确保每个用户至少被安排在一个波束成形子组中。据我们所知，文献中提出的现有两阶段预编码方案并未考虑重叠的用户分组策略，该策略可以同时解决用户选择，排序和覆盖问题。在本文中，我们提出了一种基于重叠用户分组方法的MU-MIMO两阶段预编码技术，并评估了其在面向物联网的5G环境中的计算复杂性和性能。提出的解决方案部署了两阶段预编码，其中线性零强制（ZF）预编码抑制了波束形成子组之间的干扰，非线性Tomlinson-Harashima预编码（THP）减轻了子组内的用户间干扰。重叠的用户分组方法可实现额外的容量改进，而ZF-THP预编码可在容量增益和遭受的计算复杂性之间取得平衡。与基于传统用户分组策略的两阶段预编码方案相比，该算法以较低的复杂度顺序实现了高达45％的MU-MIMO系统容量。重叠的用户分组方法可实现额外的容量改进，而ZF-THP预编码可在容量增益和遭受的计算复杂性之间取得平衡。与基于传统用户分组策略的两阶段预编码方案相比，该算法以较低的复杂度顺序实现了高达45％的MU-MIMO系统容量。重叠的用户分组方法可实现额外的容量改进，而ZF-THP预编码可在容量增益和遭受的计算复杂性之间取得平衡。与基于传统用户分组策略的两阶段预编码方案相比，该算法以较低的复杂度顺序实现了高达45％的MU-MIMO系统容量。