Modern 5G wireless cellular networks use massive multiple-input multiple-output (MIMO) technology. This concept entails using an antenna array at a base station to concurrently service many mobile devices that have several antennas on their side. In this field, a significant role is played by the precoding (beamforming) problem. During downlink, an important part of precoding is the power allocation problem that distributes power between transmitted symbols. In this paper, we consider the power allocation problem for a class of precodings that asymptotically work as regularized zero-forcing. Under some realistic assumptions, we simplify the spectral efficiency functional and obtain tractable expressions for it. We prove that equal power allocation provides optimum for the simplified functional with total power constraint (TPC). We propose low-complexity Intersection Methods (IM) that improve equal power allocation in the case of per-antenna power constraints (PAPC). On simulations using Quadriga, the proposed IM method in combination with widely-studied Water Filling (WF) shows a significant gain in spectral efficiency while using a similar computing time as the reference Equal Power (EP) solution.

翻译：现代5G无线蜂窝网络采用大规模多输入多输出（MIMO）技术。该概念的核心在于利用基站处的天线阵列，同时服务多个配备多天线的移动设备。在该领域中，预编码（波束成形）问题扮演着重要角色。在下行链路中，预编码的关键环节是功率分配问题，即在传输符号间分配功率。本文针对一类渐近等效于正则化迫零的预编码方法，研究其功率分配问题。在若干实际假设下，我们简化了频谱效率函数并获得了可解析的表达式。我们证明，在总功率约束（TPC）下，等功率分配为该简化函数提供了最优解。针对每天线功率约束（PAPC）场景，我们提出低复杂度的交叉方法（IM），该方法能改进等功率分配方案。基于Quadriga仿真平台的实验表明，所提出的IM方法与广泛研究的注水算法（WF）相结合，在保持与参考等功率分配（EP）方案相近计算时间的同时，实现了频谱效率的显著提升。