  Recent research has focused on reconfigurable intelligent surface
(RIS)-assisted cell-free systems with the goal of enhancing coverage and
lowering the cost of cell-free networks. However, current research makes the
assumption that the perfect channel state information is known. Channel
acquisition is, certainly, a difficulty in this case. This work is aimed at
investigating RIS-assisted cell-free channel estimation. Toward this end, two
unique characteristics are pointed out: 1) For all users, a common channel
exists between the base station (BS) and the RIS; and 2) For all BSs, a common
channel exists between the RIS and the user. Based on these two
characteristics, cascaded and two-timescale channel estimation concerns are
studied. Subsequently, two solutions for tackling with the two issues are
presented respectively: a three-dimensional multiple measurement vector
(3D-MMV)-based compressive sensing technique and a multi-BS cooperative
pilot-reduced methodology. Finally, simulations illustrate the effectiveness of
the schemes we have presented.
