  Intelligent Reflecting Surface (IRS) has been a promising solution to enhance
wireless networks both spectral-efficiently and energy-efficiently. This paper
considers an IRS-assisted the Internet of Things network for massive
connectivity. We aim to solve the IRS-related activity detection and channel
estimation problem which has not been studied before. In this paper, we
formulate the IRS-related activity detection and channel estimation problem as
sparse matrix factorization, matrix completion and Multiple Measurement Vector
problem and, we propose a three-stage framework based on the approximate
message passing. Simulation results verify the effectiveness of the proposed
algorithm.
