Data-Aided Channel Estimation and Combining for Cell-Free Massive MIMO With Low-Resolution ADCs

This letter aims to alleviate the impact of pilot contamination stemming from sharing pilots in cell-free massive multiple-input multiple-output (MIMO) networks with low-resolution analog-to-digital converters (ADCs). Toward this goal, we treat the decided data symbols as additional pilots and develop a data-aided channel estimator to enhance the performance of channel estimation and data detection. Furthermore, by exploiting the statistical characteristic of the estimated channel state information (CSI), we derive the analytical achievable uplink spectral efficiency (SE) for minimum mean-squared error (MMSE) combining. Numerical results show that, in comparison with the pilot-based channel estimators, the data-aided one can obtain more accurate CSI and in turn facilitate the data detection.