A Modified Structured SAMP Channel Estimation Method for FDD MIMO-OTFS Systems

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.