分布式MIMO系统多分量调制信号频率估计

Frequency estimation of multi-component modulated signal for distributed MIMO systems

  • 摘要: 针对分布式多输入多输出系统中的多频偏估计问题进行了研究,提出一种多分量调制信号的高分辨率频率盲估计方法。该方法避免了直接对多分量调制信号进行稀疏表示,无需导频等先验信息,避免传统频率估计方法中的内插、去相位混叠等处理,可一次性精确估计出所有信号频率。通过正定盲源分离方法从接收信号中分离出多个源信号,经过盲去调制处理,将其转换成多单频信号,根据多单频信号的稀疏表示,利用一个随机的压缩矩阵对信号进行压缩,再在压缩域中通过 模优化重构该稀疏信号,获得频率估计。仿真结果表明,与现有算法相比,所提方法可在少数据量、低信噪比下获得高精度估计性能,可在5dB时达到1e-6的平均均方误差。

     

    Abstract: A high resolution blind frequency estimation method for multi-component modulated signal in distributed multiple input multiple output was proposed in this paper. Did not need the prior information of pilots and avoiding sparse represent of signals, the multiple frequency offsets could be estimated once without the interpolation and phase unambiguity in traditional frequency estimation methods. The estimation of the transmitted signals from the received signals could be obtained by using the determined blind source separation according to the characteristic of distributed MIMO systems. After demodulation processing, the signals were transformed to multi-component single frequency signal. According to the sparse representation of the signal, the proposed method utilized a random compressed matrix and estimated the signal frequencies in the compressed domain by -norm optimization. Simulation results show that, the proposed method can achieve high resolution frequency estimation with large reduction in computation at low SNR comparing with existing methods. The average mean square error can achieve 1e-6 at 5dB.

     

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