Off-Grid Channel Estimation for OTFS-Based mmWave Hybrid Beamforming Systems

The combination of orthogonal-time-frequency-space (OTFS) modulation and millimeter wave (mmWave) hybrid beamforming can improve communication performance in air-to-ground high mobility systems. This letter studies a cross-domain channel estimation scheme in OTFS-based mmWave hybrid beamforming systems with off-grid parameters. First, time-domain and delay-Doppler domain signal models are established. Then, channel estimation problems are decomposed into two parallel sparse recovery problems. Finally, a sparse Bayesian learning-based block expectation-maximization algorithm is proposed to obtain the off-grid parameters. Simulation results show the preferable and robust performance of the proposed algorithm compared with existing channel estimation algorithms.