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2D-AOA Estimation and Tilt Angle Adaptation for 3D Beamforming Interference Reduction in Massive MIMO

机译:2D-AOA估计和倾斜角度适应大规模MIMO的3D波束形成干扰减小

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This paper proposes a new method based on a 2D Angle of Arrival (2D-AOA) estimation that employs 3D beamforming to eliminate the effect of interference in a Massive MIMO (M-MIMO) system. The interferences are the results of pilot contamination and spatial overlapping from nearby users. High resolution Azimuth and Elevation angles of the detected signals from Uniform Rectangular Array (URA) are used to separate the desired signal from the interfering ones without causing any change in the pilot construction of training signals. Additionally, tilt angle adaptation is employed at the base station to maximize the spectral efficiency of multi-cell M- MIMO. The performance of the proposed method is evaluated and compared with that of the conventional methods of 2D beamforming in terms of achievable sum rate. Results of the simulation demonstrate that the 3D beamforming achieved a 55% sum rate gain due to the elimination of both pilot contamination and spatial overlapping in comparison to the 24% sum rate gain achieved via the 2D beamforming method which only eliminates pilot contamination. This shows the potential of the proposed method in eliminating a large proportion of cell interference.
机译:本文提出了一种基于2D到达角度(2D-AOA)估计的新方法,该估计采用3D波束成形来消除大规模MIMO(M-MIMO)系统中干扰的影响。干扰是来自附近用户的导频污染和空间重叠的结果。来自均匀矩形阵列(URA)的检测信号的高分辨率方位角和高度角度用于将所需信号与干扰物分离,而不会导致训练信号的导频结构的任何变化。另外,在基站采用倾斜角度自适应,以最大化多电池M-MIMO的光谱效率。评估所提出的方法的性能,并与可实现的总和率的2D波束形成方法的性能进行比较。模拟结果表明,3D波束成形由于通过仅消除导频污染的2D波束形成方法而消除了飞行员污染和空间重叠,因此实现了55%的总和率增益。这表明所提出的方法在消除大部分细胞干扰方面提出的方法。

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