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

机译:大规模MIMO中3D波束成形干扰的2D-AOA估计和倾斜角度自适应

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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(2D-AOA)估计的新方法,该方法采用3D波束成形来消除大规模MIMO(M-MIMO)系统中的干扰影响。干扰是飞行员污染和附近用户空间重叠的结果。来自均匀矩形阵列(URA)的检测信号的高分辨率方位角和仰角用于将所需信号与干扰信号分开,而不会导致训练信号的导频结构发生任何变化。另外,在基站处采用倾斜角自适应以最大化多小区M-MIMO的频谱效率。评估了所提出方法的性能,并将其与传统2D波束成形方法的可实现总和率进行了比较。仿真结果表明,与通过二维波束形成方法实现的24%求和率增益(仅消除了导频污染)相比,由于消除了导频污染和空间重叠,3D波束形成实现了55%的求和率增益。这表明了所提出的方法在消除大部分小区干扰方面的潜力。

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