  Reconfigurable intelligent surfaces (RISs) have been recently considered as a
promising candidate for energy-efficient solutions in future wireless networks.
Their dynamic and lowpower configuration enables coverage extension, massive
connectivity, and low-latency communications. Due to a large number of unknown
variables referring to the RIS unit elements and the transmitted signals,
channel estimation and signal recovery in RIS-based systems are the ones of the
most critical technical challenges. To address this problem, we focus on the
RIS-assisted multi-user wireless communication system and present a joint
channel estimation and signal recovery algorithm in this paper. Specifically,
we propose a bidirectional approximate message passing algorithm that applies
the Taylor series expansion and Gaussian approximation to simplify the
sum-product algorithm in the formulated problem. Our simulation results show
that the proposed algorithm shows the superiority over a state-of-art benchmark
method. We also provide insights on the impact of different RIS parameter
settings on the proposed algorithms.
