面向毫米波波束跟踪的扩展卡尔曼滤波算法研究
Research on Extended Kalman Filter Algorithm for Millimeter Wave Beam Tracking
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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,提出一种联合 迭代优化均方误差和扩展卡尔曼滤波(Extended Kalman Filtering,EKF)的稳健波束跟踪算法。该算法首先采用EKF算法对信道增益和波束角度进行跟踪,然后基于最小均方误差准则(Minimum Mean Square Error,MMSE)对误差进行 平滑处理,以消除EKF 线性近似引入的误差,实现对波束发射角和到达角的动态跟踪。仿真结果表明所提出的算法能够明显降低移动环境中的波束跟踪误差,并具有稳健的波束跟踪能力。Abstract: For a mobile communication scenario, small misalignment between the transmitted and received beams may lead to a significant degradation of the received signal quality. This paper proposes a joint optimization of mean square error and extended Kalman filter (EKF) robust beam tracking algorithm. First, the channel complex gain and beam angle are predicted with EKF algorithm from the received signal. Secondly, we adopt the minimum mean square error (MMSE) criterion to perform iteratively optimization procedure to eliminate the estimation errors caused by the linear approximation of EKF.Simulation results demonstrate that the proposed algorithm can reduce the angle tracking error rates and increase the tracking time compared with traditional angle tracking algorithms.