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Channel estimation and optimal training with the LMMSE criterion for OFDM-based two-way relay networks

机译:基于OFDM的双向中继网络的LMMSE准则的信道估计和最佳训练

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In this paper, we consider the linear minimum mean square error (LMMSE) estimation of channel for the two-way relay network employing analog network coding and orthogonal frequency division multiplexing. The channel responses required for self-interference cancelation and coherent detection are estimated in the time domain with the preamble. We derive the optimal training condition for minimizing the mean square error (MSE) of the LMMSE estimator and obtain the corresponding MSE. It is observed that the LMMSE estimator has the optimal training condition equivalent to that of the least square estimator and that the former is less sensitive to the training sequences than the latter. We also propose new training sequences not only satisfying the optimal training condition but also providing the minimum peak-to-average power ratio.
机译:在本文中,我们考虑了采用模拟网络编码和正交频分复用的双向中继网络的信道线性最小均方误差(LMMSE)估计。自干扰消除和相干检测所需的信道响应在时域中与前同步码一起估计。我们导出了最小化LMMSE估计器的均方误差(MSE)的最佳训练条件,并获得了相应的MSE。可以看出,LMMSE估计器具有与最小二乘估计器等效的最佳训练条件,并且前者对训练序列的敏感性低于后者。我们还提出了新的训练序列,该序列不仅满足最佳训练条件,而且还提供了最小的峰均功率比。

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