Channel Estimation for Intelligent Reflecting Surface Assisted MIMO Communication

Reconfigurable Intelligent Reflecting Surface (IRS) is a promising technology for wireless cellular s beyond 5G, which can increase the throughput, the reliability, and the coverage area of the cellular network without increasing the power consumption. It also enables control on the multipath propagation environment. IRS comprises of a large number of low-cost passive reflecting elements that can smartly reconfigure the signal propagation for performance enhancement. Unlike massive MIMO systems, where the beam-steering is handled at the transmitter and/or the receiver, IRS will steer the beams to the desired user, as a simple reflection without any amplification, decoding, encoding, processing, or noise added. However, to keep IRS completely passive, the channel estimation task should be carried out at the transmitter or at the receiver device. This is not an easy task because of the presence of the IRS in the communication model, and to the best of our knowledge, this is still an open problem, and there are few trials in the literature but the optimality of these approaches, and the associated complexity versus performance versus estimation overhead trade-offs are open research issues. Moreover, in general, the design of an efficient channel estimation and feedback protocol that make the IRSs as passive as possible, and the understanding of the associated performance versus complexity trade-offs are not known yet.