Doubly-Iterative Sparsified MMSE Turbo Equalization for OTFS Modulation

Currently, orthogonal time frequency space (OTFS) modulation has drawn much attention to reliable communications in high-mobility scenarios. This paper proposes a doubly-iterative sparsified minimum mean square error (DI-S-MMSE) turbo equalizer, which iteratively exchanges the extrinsic information between soft-input-soft-input (SISO) MMSE estimator and SISO decoder. Our proposed equalizer does not suffer from short loops approaches performance of near-optimal symbol-wise maximum posteriori (MAP) algorithm. To exploit inherent sparsity OTFS system, we resort graph theory investigate pattern channel matrix, propose two sparsification guidelines reduce complexity calculating matrix inverse at estimator. Then, apply iterative algorithms estimation, i.e., Generalized Minimal Residual (GMRES) Factorized Sparse Approximate Inverse (FSPAI) algorithms. The former is used initial iteration, whose global convergence proven our while latter subsequent iterations with help guidelines. Simulation results demonstrate that can achieve good bit-error-rate (BER) regardless fractional Doppler, only linear order complexity.