A Modified Structured SAMP Channel Estimation Method for FDD MIMO-OTFS Systems
X.L. Li, Chengzhao Shan, Honglin Zhao, Weijie Yuan, Ruoyu Zhang
Abstract
Orthogonal time frequency space (OTFS) modulation has been proposed to provide users with stable and reliable services in high-mobility scenarios. The sparse representation of channels in OTFS makes it possible to obtain accurate channel state information with a small number of pilots by compressed sensing (CS) algorithms. However, conventional CS algorithms in MIMO-OTFS channel estimation schemes assume that channel sparsity K is known, which is often not available in practical scenarios. In this letter, we propose a structured sparsity adaptive matching pursuit (SSAMP) algorithm for MIMO-OTFS channel estimation without the prior information of the channel sparsity K. On this basis, we further propose a modified structured sparsity adaptive matching pursuit algorithm to improve both the channel estimation accuracy and reconstruction speed. Simulation results show that the proposed algorithms are effective.