Tensor-Based Low-Complexity Channel Estimation for mmWave Massive MIMO-OTFS Systems

摘要

Orthogonal time frequency space(OTFS)modulation,collaborated with millimeter-wave(mmWave)massive multiple-input-multiple-output(MIMO),is a promising technology for next generation wireless communications in high mobility scenarios.However,one of the main challenges for mmWave massive MIMO-OTFS systems is the enormous computational complexity of channel estimation incurred by the huge OTFS symbol size and the large number of antennas.To address this issue,in this paper,a tensor-based orthogonal matching pursuit(OMP)channel estimation algorithm is proposed by exploiting the channel sparsity in the delay-Doppler-angle domain.In particular,we firstly propose a novel pilot design for the OTFS symbol structure in the frequency-time domain.Then,based on the proposed pilot structure,we formulate the channel estimation as a sparse signal recovery problem,and the tensor decomposition and parallel support detection are introduced into the tensor-based OMP algorithm to reduce the signal processing dimension significantly.Numerical simulations are performed to verify the superiority and the robustness of the proposed tensor-based OMP algorithm.