Publication | Open Access
Reconfigurable Intelligent Surfaces: Potentials, Applications, and Challenges for 6G Wireless Networks
16
Citations
14
References
2021
Year
6G NetworksEngineering5G SystemCommunication EngineeringEdge ComputingAntennaComputer EngineeringReconfigurable Intelligent Surfaces6GWireless NetworksMobile ComputingInternet Of ThingsWireless ComputingChannel Access MethodTechnologyRadio Access ProtocolChannel EstimationSmart Wireless Network
Reconfigurable intelligent surfaces (RISs) enable smart radio environments and are emerging as an energy‑efficient, cost‑effective technology to meet future wireless demands. This tutorial reviews RISs for 6G, covering performance gains, practical implementation challenges, NOMA integration under imperfect CSI, and future research directions. RISs employ many low‑cost passive reflecting elements that impose phase shifts on incident signals to shape the propagation channel between transmitter and receiver. Numerical results demonstrate that accurate channel estimation is essential for RIS‑assisted networks and that RIS size depends on multiple influencing factors.
Reconfigurable intelligent surfaces (RISs), with the potential to realize smart radio environments, have emerged as an energy-efficient and a cost-effective technology to support the services and demands foreseen for coming decades. By leveraging a large number of low-cost passive reflecting elements, RISs introduce a phase-shift in the impinging signal to create a favorable propagation channel between the transmitter and the receiver. In this article, we provide a tutorial overview of RISs for sixth-generation (6G) wireless networks. Specifically, we present a comprehensive discussion on performance gains that can be achieved by integrating RISs with emerging communication technologies. We address the practical implementation of RIS-assisted networks and expose the crucial challenges, including the RIS reconfiguration, deployment and size optimization, and channel estimation. Furthermore, we explore the integration of RIS and non-orthogonal multiple access (NOMA) under imperfect channel state information (CSI). Our numerical results illustrate the importance of better channel estimation in RIS-assisted networks and indicate the various factors that impact the size of RIS. Finally, we present promising future research directions for realizing RIS-assisted networks in 6G communication.
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