This paper proposes a scalar ambiguity estimation method that sublimates the blind channel estimation method to totally blind estimation. Generally, the blind channel estimation method can identify the channel impulse response or channel frequency response up to scalar ambiguity. For coherent detection, the ambiguity should also be estimated. Exploiting the multiple modulation scheme, we estimate the scalar ambiguity for zero forcing equalization by maximum likelihood (ML). We also detect some equalized symbols fed into the ML estimation, which reduces the computational complexity of the proposed scalar ambiguity estimation. To efficiently reduce the complexity, we derive the Bayesian Cramér Rao lower bound (BCRB) of the ambiguity estimation. When evaluated in computational simulations, the performance of the proposed method achieved the BCRB performance at high signal-to-noise ratios. We also confirmed that when the proposed method is combined with the existing blind channel estimation, coherent detection is possible without any pilot symbols.

中文翻译：

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块传输系统中基于最大似然准则的标量模糊度估计

本文提出了一种标量模糊度估计方法，将盲信道估计方法升华为完全盲估计。通常，盲信道估计方法可以识别直至标量模糊度的信道冲激响应或信道频率响应。对于相干检测，还应该估计歧义。利用多重调制方案，我们通过最大似然（ML）估计了零强迫均衡的标量歧义。我们还检测到一些输入到ML估计中的均衡符号，这降低了提出的标量模糊度估计的计算复杂度。为了有效地降低复杂度，我们导出了模糊度估计的贝叶斯CramérRao下界（BCRB）。在计算仿真中进行评估时，该方法的性能在高信噪比下实现了BCRB性能。我们还确认，当将所提出的方法与现有的盲信道估计结合使用时，无需任何导频符号就可以进行相干检测。