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MAX-SLNR Precoding Algorithm for Massive MIMO System

机译:大规模MIMO系统的MAX-SLNR预编码算法

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Pilot Contamination obviously degrades the system performance of Massive MIMO systems. In this paper, a downlink precoding algorithm based on the Signal-to- Leakage-plus-Noise-Ratio (SLNR) criterion is put forward. First, the impact of Pilot Contamination on SLNR is analyzed,then the precoding matrix is calculated with the eigenvalues decomposition of SLNR, which not only maximize the array gains of the target user, but also minimize the impact of Pilot Contamination and the leak to the users of other cells. Further, a simplified solution is derived, in which the impact of Pilot Contamination can be suppressed only with the large-scale fading coefficients. Simulation results reveal that: in the scenario of the serious pilot contamination, the proposed algorithm can avoid the performance loss caused by the pilot contamination compared with the conventional Massive MIMO precoding algorithm. Thus the proposed algorithm can acquire the perfect performance gains of Massive MIMO system and has better practical value since the large-scale fading coefficients are easy to measure and feedback.
机译:飞行员污染显然会降低Massive MIMO系统的系统性能。提出了一种基于信噪比(SLNR)准则的下行预编码算法。首先,分析了飞行员污染对SLNR的影响,然后利用SLNR的特征值分解来计算预编码矩阵,这不仅使目标用户的阵列增益最大化,而且使飞行员污染的影响以及对泄漏的泄漏最小化。其他单元的用户。此外,推导了一种简化的解决方案,其中仅通过大规模衰落系数就可以抑制飞行员污染的影响。仿真结果表明:与传统的Massive MIMO预编码算法相比,在严重导频污染的情况下,该算法可以避免导频污染造成的性能损失。由于大规模衰落系数易于测量和反馈,因此该算法能够获得Massive MIMO系统的理想性能增益,具有较好的实用价值。

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