Bayesian Learning Aided Sparse Channel Estimation for Orthogonal Time Frequency Space Modulated Systems

A novel sparse channel state information (CSI) estimation scheme is proposed for orthogonal time frequency space (OTFS) modulated systems, in which the pilots are directly transmitted over time-frequency (TF)-domain grid estimating delay-Doppler (DD)-domain CSI. The CSI model leads to a reduction pilot overhead as well training duration required. Furthermore, it does not require DD-domain guard interval between and data symbols, hence increasing bandwidth efficiency. Bayesian learning (BL) framework acquisition, exploits sparsity improving accuracy comparison conventional minimum mean squared error (MMSE)-based scheme. low-complexity linear MMSE detector used subsequent detection phase. Our simulation results demonstrate performance improvement of BL-based MMSE-based other existing schemes.