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Although it is often used in the orthogonal frequency division multiplexing(OFDM) systems, application of massive multiple-input multiple-output (MIMO)over the orthogonal time frequency space (OTFS) modulation could suffer fromenormous training overhead in high mobility scenarios. In this paper, wepropose one uplink-aided high mobility downlink channel estimation scheme forthe massive MIMO-OTFS networks. Specifically, we firstly formulate the timedomain massive MIMO-OTFS signal model along the uplink and adopt theexpectation maximization based variational Bayesian (EM-VB) framework torecover the uplink channel parameters including the angle, the delay, theDoppler frequency, and the channel gain for each physical scattering path.Correspondingly, with the help of the fast Bayesian inference, one low complexapproach is constructed to overcome the bottleneck of the EM-VB. Then, we fullyexploit the angle, delay and Doppler reciprocity between the uplink and thedownlink and reconstruct the angles, the delays, and the Doppler frequenciesfor the downlink massive channels at the base station. Furthermore, we examinethe downlink massive MIMO channel estimation over the delay-Doppler-angledomain. The channel dispersion of the OTFS over the delay-Doppler domain iscarefully analyzed. Various numerical examples are presented to confirm thevalidity and robustness of the proposed scheme.

Uplink-aided High Mobility Downlink Channel Estimation over Massive MIMO-OTFS System