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Two dimension angle of arrival-based precoding for pilot contamination reduction in multi-cell massive MlMO systems

机译:基于到达的两维角度,用于多电池大量MLMO系统中的导频污染降低的预编码

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This paper proposes a new precoding approach that utilizes two-dimension (2D) Angle of Arrival (AOA) based precoding (beamforming) approach for multi-cell massive Multiple Input Multiple Output (m-MIMO) systems. The proposed approach enhances the performance of m-MIMO systems by overcoming pilot contamination that is caused by corrupted Channel State Information. It exploits the spatial properties of the propagated signals to distinguish between various users in the multi-cell m-MIMO system and selects the partial space for beamforming based on AOA information to suppress inter-cell and intra-cell interference. We mathematically analyze the impact of pilot contamination in the uplink training and determine the closed-form approximation of uplink Minimum Mean Square Error (MMSE) estimator. By using MMSE estimator as well as 2D AOA and channel estimation, a corresponding MMSE precoding which minimizes the effect of pilot contamination and improves the downlink achievable rate of the system is proposed. Furthermore, a comparison is made of the resolution between the various 2D AOA estimations for an m-MIMO and the optimum values closest bound for the proposed precoding was chosen to reduce pilot contamination. The performance of the proposed MMSE precoding based on 2D AOA estimation methods: 2D Unitary Estimation of Signal Parameters via Rotational Invariance Techniques (2D UESPRIT), 2D Fourier Domain Line Search MUSIC (2D FDLSM), and 2D Propagator Method (2D PM)) were evaluated and compared with pilot contaminated system and deterministic MMSE precoding in terms of their respective achievable rate. Simulation results reveal that the achievable sum rate gains of 2D UESPRIT, 2D FDLSM, and 2D PM based precoding which achieved 97.6%, 92.4%, 86.3% of the desired deterministic performance, respectively, compared to pilot contaminated system, which achieved only 90% even when in the best case of having only one contaminated user out of all users within the activated cell. Findings from our research indicate the feasibility of utilizing the AOA based beamforming to reduce pilot contamination effect that is inherent in a larger order m-MIMO system for the Fifth Generation (5G) wireless transmissions.
机译:本文提出了一种新的预编码方法,其利用基于三维(2D)到达(AOA)的预编码(AOA)的预编码(波束成形)方法进行多电池大量多输入多输出(M-MIMO)系统。所提出的方法通过克服由损坏的信道状态信息引起的导频污染来增强M-MIMO系统的性能。它利用传播信号的空间特性来区分多小区M-MIMO系统中的各种用户,并基于AOA信息选择用于抑制小区间和电池内干扰的部分空间。我们在数学上分析导频污染在上行训练中的影响,并确定上行链路最小均方误差(MMSE)估计器的闭合形式近似。通过使用MMSE估计以及2D AOA和信道估计,提出了一种相应的MMSE预编码,其最小化了导频污染的效果并提高了系统的下行链路可实现的速率。此外,选择比较M-MIMO的各种2D AOA估计之间的分辨率,并且选择了所提出的预编码的最接近界定的最佳值以减少导频污染。基于2D AOA估计方法的提出的MMSE预编码的性能:2D通过旋转不变性技术(2D UESPRIT),2D傅立叶域线搜索音乐(2D FDLSM)和2D传播者方法(2D PM))的信号参数的酉估计与试验污染系统进行评估,并在各自可实现的速率方面进行确定的MMSE预编码。仿真结果表明,与先导污染系统相比,2D UESprit,2D FDLSM和2D PM的预编码可实现的2D FDLSM和2D PM的预编码的增益分别实现了97.6%,占所需的确定性性能的97.6%,86.3%即使在最佳情况下只有一个受污染的用户在激活的小区内的所有用户中。我们的研究结果表明,利用基于AOA的波束成形来降低用于第五代(5G)无线传输的较大阶M-MIMO系统所固有的导频污染效果的可行性。

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