To achieve the joint active and passive beamforming gains in the reconfigurable intelligent surface assisted millimeter wave system, the reflected cascade channel needs to be accurately estimated. Many strategies have been proposed in the literature to solve this issue. However, whether the Cramér-Rao lower bound (CRLB) of such estimation is achievable still remains uncertain. To fill this gap, we first convert the channel estimation problem into a sparse signal recovery problem by utilizing the properties of discrete Fourier transform matrix and Kronecker product. Then, a joint typicality-based estimator is utilized to carry out the signal recovery task. We show that, through both mathematical proofs and numerical simulations, the solution proposed in this letter can asymptotically achieve the CRLB.

中文翻译：

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可重构智能表面辅助通信系统信道估计的 Cramér-Rao 下界的渐近可实现性

为了在可重构智能表面辅助毫米波系统中实现主动和被动波束形成的联合增益，需要准确估计反射级联信道。文献中提出了许多策略来解决这个问题。然而，这种估计的 Cramér-Rao 下限 (CRLB) 是否可实现仍然不确定。为了填补这一空白，我们首先利用离散傅立叶变换矩阵和 Kronecker 积的性质将信道估计问题转换为稀疏信号恢复问题。然后，利用基于联合典型性的估计器来执行信号恢复任务。我们表明，通过数学证明和数值模拟，这封信中提出的解决方案可以渐近地实现 CRLB。