  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.
