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首页> 外文期刊>Progress in Artificial Intelligence >Low-Complexity Joint Channel Estimation for Multi-User mmWave Massive MIMO Systems
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Low-Complexity Joint Channel Estimation for Multi-User mmWave Massive MIMO Systems

机译:多用户MMWAVE大规模MIMO系统的低复杂性关节通道估计

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摘要

For multi-user millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, the precise acquisition of channel state information (CSI) is a huge challenge. With the increase of the number of antennas at the base station (BS), the traditional channel estimation techniques encounter the problems of pilot training overhead and computational complexity increasing dramatically. In this paper, we develop a step-length optimization-based joint iterative scheme for multi-user mmWave massive MIMO systems to improve channel estimation performance. The proposed estimation algorithm provides the BS with full knowledge of all channel parameters involved in up- and down-links. Compared with existing algorithms, the proposed algorithm has higher channel estimation accuracy with low complexity. Moreover, the proposed scheme performs well even with a small number of training sequences and a large number of users. Simulation results are shown to demonstrate the performance of the proposed channel estimation algorithm.
机译:对于多用户毫米波(MMWAVE)大规模多输入多输出(MIMO)系统,频道状态信息(CSI)的精确获取是一个巨大的挑战。随着基站(BS)的天线数量的增加,传统信道估计技术遇到了导频训练开销和计算复杂性的问题急剧增加。在本文中,我们开发了一种基于步长优化的基于多用户MMWave MATMOM MIMO系统的联合迭代方案,以提高信道估计性能。所提出的估计算法提供了BS,全面了解了上下链路中涉及的所有通道参数。与现有算法相比,所提出的算法具有较高的信道估计精度,具有低复杂度。此外,所提出的方案即使具有少量训练序列和大量用户,也表现良好。示出了仿真结果证明了所提出的信道估计算法的性能。

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