A Stochastic Framework of Millimeter Wave Signal for Mobile Users: Experiment, Modeling and Application in Beam Tracking

Yawen Fan, Jingchao Li, Husheng Li, Chao Tian
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引用次数: 3

Abstract

In this paper, we propose to employ the Markov jump linear system to model the characteristics of millimeter wave (mmWave) signals, such as signal strength and angle-of-arrival (AoA), for mobile users. We integrate the spatial correlation between line-of-sight (LoS) and none-line-of-sight (NLoS) beams to the stochastic framework for better modeling mmWave. To handle the channel dynamics in mmWave communications, we derive a Markov gain-state channel model based on channel measurements in an indoor environment from our field measurement. The proposed stochastic model is used to estimate the transition probability of each channel. Then it is integrated into the Markov jump linear system framework to construct the linear estimator for channel variables, such as AoA and channel gain. The simulation result demonstrates the outperformance of the proposed framework against the previous Kalman-filtering-based tracking algorithm.
移动用户毫米波信号随机框架:实验、建模及其在波束跟踪中的应用
在本文中,我们建议使用马尔可夫跳变线性系统来模拟毫米波(mmWave)信号的特性,如信号强度和到达角(AoA),用于移动用户。我们将视线(LoS)和非视线(NLoS)波束之间的空间相关性整合到随机框架中,以便更好地建模毫米波。为了处理毫米波通信中的信道动态,我们从现场测量中导出了基于室内环境中信道测量的马尔可夫增益状态信道模型。提出的随机模型用于估计每个信道的转移概率。然后将其集成到马尔可夫跳变线性系统框架中,构造信道方差和信道增益等信道变量的线性估计器。仿真结果表明,该框架相对于先前基于卡尔曼滤波的跟踪算法具有优异的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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