Reconfigurable Intelligent Surfaces and Metamaterials: The Potential of Wave Propagation Control for 6G Wireless Communications

Abstract

The future 6G of wireless communication networks will have to meet multiple requirements in increasingly demanding levels, either individually or in combinations in small groups. This trend has spurred recent research activities on transceiver hardware architectures and novel wireless connectivity concepts. Among the emerging wireless hardware architectures belong the Reconfigurable Intelligent Surfaces (RISs), which are artificial planar structures with integrated electronic circuits that can be programmed to manipulate an incoming ElectroMagnetic (EM) field in a wide variety of functionalities. Incorporating RISs in wireless networks has been recently advocated as a revolutionary means to transform any naturally passive wireless communication environment to an active one. This can be accomplished by deploying cost-effective and easy to coat RISs to the environment's objects (e.g., building facades and indoor walls/ceilings), thus, offering increased environmental intelligence for the scope of diverse wireless networking objectives. In this paper, we first provide a brief history on wave propagation control for optics and acoustics, and overview two representative indoor wireless trials at 2.47GHz for spatial EM modulation with a passive discrete RIS. The first trial dating back to 2014 showcases the feasibility of highly accurate spatiotemporal focusing and nulling, while the second very recent one demonstrates that passive RISs can enrich multipath scattering, thus, enabling throughput boosted communication links. Motivated by the late research excitement on the RIS potential for intelligent EM wave propagation modulation, we describe the status on RIS hardware architectures and present key open challenges and future research directions for RIS design and RIS-empowered 6G wireless communications.

9 pages; 7 figures; IEEE ComSoc TCCN Newsletter, vol. 6, no. 1, June 2020

References in corpus (3)

• Phase control algorithms for focusing light through turbid media
• Analysis of a Waveguide-Fed Metasurface Antenna
• Resonant Metalenses for Breaking the Diffraction Barrier

Cited by in corpus (5)

• Lyapunov-Driven Deep Reinforcement Learning for Edge Inference Empowered by Reconfigurable Intelligent Surfaces
• Active Reconfigurable Intelligent Surface Aided Wireless Communications
• Non-Coherent Modulation for RIS-Empowered Multi-Antenna OFDM Communications
• Planning Mm-Wave Access Networks With Reconfigurable Intelligent Surfaces
• Joint Channel Estimation and Signal Recovery in RIS-Assisted Multi-User MISO Communications