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 Cram\'er-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 in fact asymptotically achieve the CRLB.

翻译：为了在可重新配置的智能表面辅助毫米波系统中实现联合主动和被动波束增益,需要准确估计反射级联频道。文献中已经提出了解决这一问题的许多战略。然而,这种估算的Cram\'er-Rao较低约束值(CRLB)是否仍然可以实现仍然不确定。为了填补这一空白,我们首先利用离散的Fourier变异矩阵和Kronecker产品的特性,将频道估计问题转化为稀有的信号恢复问题。然后,利用基于典型的联合估计器执行信号恢复任务。我们表明,通过数学证明和数字模拟,本信中提出的解决办法实际上可以同时实现CRLB。