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In this letter, we investigate channel estimation for wideband millimeter-wave (mmWave) massive multiple-input multiple-output under hybrid architecture with low-precision analog-to-digital converters (ADCs). To design channel estimation for the hybrid structure, both analog processing components and frequency-selective digital combiners need to be optimized. The proposed channel estimator follows the typical linear-minimum-mean-square-error structure and applies for an arbitrary channel model. Moreover, for sparsity channels as in mmWave, the proposed estimator performs more efficiently by incorporating orthogonal matching pursuit to mitigate quantization noise caused by low-precision ADCs. Consequently, the proposed estimator outperforms conventional ones as demonstrated by computer simulation results.
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Wang et al. (2018) studied this question.
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