  Reconfigurable intelligent surfaces (RISs) have attracted great attention as
a potential beyond 5G technology. These surfaces consist of many passive
elements of metamaterials whose impedance can be controllable to change the
phase, amplitude, or other characteristics of wireless signals impinging on
them. Channel estimation is a critical task when it comes to the control of a
large RIS when having a channel with a large number of multipath components. In
this paper, we propose a novel channel estimation scheme that exploits spatial
correlation characteristics at both the massive multiple-input multiple-output
(MIMO) base station and the planar RISs, and other statistical characteristics
of multi-specular fading in a mobile environment. Moreover, a novel heuristic
for phase-shift selection at the RISs is developed, inspired by signal
processing methods that are effective in conventional massive MIMO. Simulation
results demonstrate that the proposed uplink RIS-aided framework improves the
spectral efficiency of the cell-edge mobile users substantially in comparison
to a conventional single-cell massive MIMO system.
