This paper focuses on mobile multi-input multi-output (MIMO) underwater acoustic communications (UAC) over double-selective channels suffering from both inter-symbol interference and Doppler scaling effects (stretching or compression). Temporal resampling is implemented to effectively convert the Doppler scaling effects to Doppler frequency shifts. Then an extension of the sparse learning via iterative minimization (SLIM) algorithm, referred to as generalization of SLIM (GoSLIM), is used to estimate the frequency modulated acoustic channels. Because GoSLIM is user parameter free, it is easy to use in practical applications. We also consider channel equalization and symbol detection for various MIMO transmission schemes, including both space-time block coding and spatial multiplexing. The effectiveness of the proposed mobile MIMO UAC schemes is demonstrated using recently acquired in-water experimental measurements.
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