Estimation Of Channels In Systems With Intelligent Reflecting Surfaces

We consider channel estimation for systems equipped with an intelligent reflecting surface (IRS). We develop least squares (LS) and minimum mean square error (MMSE) estimation for such systems. The appropriate system models are developed and we also discuss the parameters which can be estimated in such a setup because there exists a difficulty due to the ambiguity for the two channels connecting with the IRS. The MMSE estimator is based on a Kronecker product approximation of the channel covariance matrix. The simulations results illustrate the advantage of the optimized pilots and the optimized phase allocations for the channel estimation.