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In a cell-free cloud radio access network (C-RAN) architecture, uplinkchannel estimation is carried out by a centralized baseband processing unit(BBU) connected to distributed remote radio heads (RRHs). When the RRHs havemultiple antennas and limited radio front-end resources, the design of uplinkchannel estimation is faced with the challenges posed by reduced radiofrequency (RF) chains and one-bit analog-to-digital converters (ADCs) at theRRHs. This work tackles the problem of jointly optimizing the pilot sequencesand the pre-RF chains analog combiners with the goal of minimizing the sum ofmean squared errors (MSEs) of the estimated channel vectors at the BBU. Theproblem formulation models the impact of the ADC operation by leveragingBussgang's theorem. An efficient solution is developed by means of an iterativealternating optimization algorithm. Numerical results validate the advantagesof the proposed joint design compared to baseline schemes that randomly chooseeither pilots or analog combiners.

Optimizing Pilots and Analog Processing for Channel Estimation in Cell-Free Massive MIMO With One-Bit ADCs