毫米波移动通信中基于AUKF的波束跟踪算法
投稿时间:2020-04-01  修订日期:2020-06-26  点此下载全文
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作者单位E-mail
彭章友 上海大学 特种光纤与光接入网省部共建教育部重点实验室 zypeng@i.shu.edu.cn 
李文 上海大学 特种光纤与光接入网省部共建教育部重点实验室 vector@t.shu.edu.cn 
中文摘要:针对移动毫米波通信场景中收发波束存在角度偏差时接收信号质量急剧下降的问题,提出一种基于自适应无迹卡尔曼滤波(AUKF)原理的波束跟踪算法。针对低复杂度对于移动场景的适用性,该算法设计了一种有效的波束跟踪方案,在模拟波束形成架构中通过训练一个波束对以跟踪一条电磁波路径来保持有效的毫米波通信。通过引入自适应调节因子,在系统存在异常扰动时候,可以自适应调节预测和观测协方差矩阵,提高估计精度和收敛速度。仿真结果表明,所提的自适应无迹卡尔曼滤波算法明显降低了移动环境中的波束跟踪误差,具有稳健的波束跟踪能力。
中文关键词:毫米波MIMO系统  模拟波束赋形 波束跟踪  自适应UKF
 
AUKF-based beam tracking algorithm in Millimeter-Wave mobile communication
Abstract:Aiming at the problem that the received signal quality drops sharply when the transmit and receive beams have angular deviations in a mobile millimeter wave communication scenario, this paper proposes a beam tracking algorithm based on Adaptive Unscented Kalman Filter (AUKF). Considering the applicability of low complexity for mobile scenarios, this algorithm designs an effective beam tracking scheme. In the analog beamforming architecture, a beam pair is trained to track an electromagnetic wave path to maintain effective millimeter wave communication. By introducing an adaptive adjustment factor, the prediction and observation covariance matrices can be adjusted adaptively when there is an abnormal disturbance in the system, improving the estimation accuracy and the convergence speed. Simulation results show that the adaptive Unscented Kalman Filter algorithm in this paper significantly reduces beam tracking errors in mobile environments and has robust beam tracking capabilities.
keywords:Millimeter-Wave MIMO system  analog beamforming  beam tracking  adaptive UKF
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