In this letter, we propose an efficient channel estimation method for multiple input multiple output orthogonal time-frequency-space systems in which each delay path cluster of the channel has multiple Dopplers.… Click to show full abstract
In this letter, we propose an efficient channel estimation method for multiple input multiple output orthogonal time-frequency-space systems in which each delay path cluster of the channel has multiple Dopplers. Under the channel model, the relationship between the input and output in the delay-Doppler (DD) domain is first analysed. Thereafter, based on the channel characteristics of the DD domain, we cast the channel estimation problem as a block sparse signal recovery problem, which is solved by the proposed block sparse Bayesian learning with block reorganization (BSBL-BR) method. In contrast to the traditional BSBL method, we update iteratively the size of non-sparse blocks to obtain a better channel estimation accuracy. Simulation results demonstrate the effectiveness and superiority of the proposed method over state-of-the-art methods in terms of system performance and noise robustness.
               
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