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Polarization Channel Estimation for Circular and Non-Circular Signals in Massive MIMO Systems

机译:大规模MIMO系统中圆形和非圆形信号的极化信道估计

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The polarization millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) system has been deployed in next-generation wireless communication since it can provide a high-data stream and high space efficiency simultaneously. Polarization channel parameter estimation for polarized mmWave massive MIMO systems is extremely important for directional beamforming with data transmissions. In this paper, the base station (BS) equipped with a large polarization-sensitive array is considered in massive MIMO systems. The polarization channel consists of direction-of-arrival (DOA) and polarization parameters that are estimated from the coexistence of circular and non-circular signals. Based on the unconjugated covariance matrix, the initialized polarization channel estimation is achieved by multiple signal classification (MUSIC). Then, the high-accuracy polarization channel estimation for general non-circular rate signals is performed by reconstructing the corresponding noise matrix. The high-accuracy polarization channel estimation for circular signals is obtained based on covariance matrix differencing. Moreover, the dimension of parameter search is reduced based on the partial derivative of the spectrum function with respect to the non-circular phase. The high-accuracy polarization channel estimation for the maximum non-circular rate signal is finally achieved based on the initialized parameter estimation of the polarization channel. The proposed algorithm estimates different kinds of signals separately. The effect of different kinds of signals is reduced significantly, which means that the resolution probability of different kinds of signals can be dramatically improved. Numerical examples are provided to demonstrate the performance of the proposed algorithm, especially in small angular distances.
机译:极化毫米波(mmWave)大规模多输入多输出(MIMO)系统已经部署在下一代无线通信中,因为它可以同时提供高数据流和高空间效率。极化mmWave大规模MIMO系统的极化信道参数估计对于数据传输的定向波束形成极为重要。在本文中,考虑在大型MIMO系统中配备大型极化敏感阵列的基站(BS)。极化通道由到达方向(DOA)和极化参数组成,这些参数是根据圆形和非圆形信号的共存估计的。基于非共轭协方差矩阵,可通过多信号分类(MUSIC)来实现初始化的极化信道估计。然后,通过重构相应的噪声矩阵来执行用于一般非圆形速率信号的高精度极化信道估计。基于协方差矩阵差分,获得了用于圆形信号的高精度极化信道估计。此外,基于谱函数相对于非圆形相位的偏导数,减小了参数搜索的尺寸。最终基于极化信道的初始化参数估计,实现了针对最大非圆形速率信号的高精度极化信道估计。所提出的算法分别估计不同种类的信号。大大降低了各种信号的影响,这意味着可以大大提高各种信号的分辨率。提供了数值示例来证明所提出算法的性能,尤其是在小角度距离内。

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