  Achieving high channel estimation accuracy and reducing hardware cost as well
as power dissipation constitute substantial challenges in the design of massive
multiple-input multiple-output (MIMO) systems. To resolve these difficulties,
sophisticated pilot designs have been conceived for the family of
energy-efficient hybrid analog-digital (HAD) beamforming architecture relying
on adaptive-resolution analog-to-digital converters (RADCs). In this paper, we
jointly optimize the pilot sequences, the number of RADC quantization bits and
the hybrid receiver combiner in the uplink of multiuser massive MIMO systems.
We solve the associated mean square error (MSE) minimization problem of channel
estimation in the context of correlated Rayleigh fading channels subject to
practical constraints. The associated mixed-integer problem is quite
challenging due to the nonconvex nature of the objective function and of the
constraints. By relying on advanced fractional programming (FP) techniques, we
first recast the original problem into a more tractable yet equivalent form,
which allows the decoupling of the fractional objective function. We then
conceive a pair of novel algorithms for solving the resultant problems for
codebook-based and codebook-free pilot schemes, respectively. To reduce the
design complexity, we also propose a simplified algorithm for the
codebook-based pilot scheme. Our simulation results confirm the superiority of
the proposed algorithms over the relevant state-of-the-art benchmark schemes.
