5 research outputs found
Is Channel Estimation Necessary to Select Phase-Shifts for RIS-Assisted Massive MIMO?
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
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 novel
channel estimation schemes for different RIS-assisted massive multiple-input
multiple-output (MIMO) configurations. The proposed methods exploit spatial
correlation characteristics at both the 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. For the RIS-assisted massive MIMO, a new receive combining method
and a fixed-point algorithm, which solves the max-min fairness power control
optimally, are proposed. Simulation results demonstrate that the proposed
uplink RIS-aided framework improves the spectral efficiency of the cell-edge
mobile user equipments substantially in comparison to a conventional
single-cell massive MIMO system. The impact of several channel effects are
studied to gain insight about which RIS configuration is preferable and when
the channel estimation is necessary to boost the spectral efficiency.Comment: 30 pages, 9 figures, submitted to IEEE Journa