PHY-Layer Design Challenges in Reconfigurable Intelligent Surface Aided 6G Wireless Networks

Reconfigurable intelligent surfaces (RISs), made of nearly-passive, low-cost, and reconfigurable meta-materials, can artificially customize the propagation environment by introducing controllable and independent phase shifts on electromagnetic waves. Integrating RISs into 6G wireless networks leads to unprecedented energy focusing at receivers, and hence significantly enhances the primary communications. This chapter first overviews the new PHY-layer design challenges accompanying RIS-aided 6G communications. Particularly, channel estimation in RIS-aided systems is more challenging than that in traditional communication systems, since the nearly-passive RISs have very limited capability of receiving, processing, and transmitting incident signals. This chapter further illustrates two state-of-the-art approaches for estimating the cascaded transmitter-RIS and RIS-receiver channels by exploiting channel structural features in RIS-aided systems. Specifically, the first approach artificially introduces signal sparsity by controlling the on/off states of the RIS elements, and estimates the cascaded channels by sparse matrix factorization and matrix completion. The second approach directly factorizes the cascaded channels by exploiting the slow-varying information of the RIS-receiver channel and the inherent sparsity of the transmitter-RIS channel. Finally, this chapter discusses open issues in RIS channel estimation and concludes with future research directions.