Low complexity ml augmented robust channel estimation

Abstract

A method includes acquiring, by a processor of an electronic device, information associated with channel and noise covariances. The method includes determining one or more time-domain rectangular filters based on the information associated with the channel and noise covariances. The method includes generating one or more convolutional kernels based on the one or more rectangular filters applied to the channel and noise covariances in a time-domain. The method includes generating a codebook based on the one or more convolutional kernels, the codebook comprising N codewords. Further, the method can include establishing a communication link to a gNB configured to: receive a reference signal from a user equipment; receive the codebook; calculate channel statistics using a low complexity algorithm; execute a decision tree classifier to select a codeword from the codebook stored in memory of the gNB; and apply the selected codeword as convolution kernel for channel estimation.