Estimation Of Channels In Systems With Intelligent Reflecting Surfaces
Michael Joham, Hangze Gao, Wolfgang Utschick
2022ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)17 citationsDOI
Abstract
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.
Topics & Concepts
EstimatorChannel (broadcasting)Kronecker productCovariance matrixComputer scienceMean squared errorAmbiguityMinimum mean square errorKronecker deltaAlgorithmCovarianceLeast-squares function approximationMathematical optimizationMathematicsStatisticsTelecommunicationsPhysicsQuantum mechanicsProgramming languageAdvanced Wireless Communication TechnologiesSatellite Communication SystemsOptical Wireless Communication Technologies