Hybrid Reconfigurable Intelligent Metasurfaces: Enabling Simultaneous Tunable Reflections and Sensing for 6G Wireless Communications

Current discussions on the sixth Generation (6G) of wireless communications are envisioning future networks as a unified communication, sensing, and computing platform that intelligently enables diverse services, ranging from immersive to mission critical applications. The recently conceived concept of the smart radio environment, enabled by Reconfigurable Intelligent Surfaces (RISs), contributes towards this intelligent networking trend, offering programmable propagation of information-bearing signals, which can be jointly optimized with transceiver operations. Typical RIS implementations include metasurfaces with nearly passive meta-atoms, allowing to solely reflect the incident wave in an externally controllable way. However, this purely reflective nature induces significant challenges in the RIS orchestration from the wireless network. For example, channel estimation, which is essential for coherent communications in RIS-empowered wireless networks, is quite challenging with the available RIS designs. This article introduces the concept of Hybrid reflecting and sensing RISs (HRISs), which enables metasurfaces to reflect the impinging signal in a controllable manner, while simultaneously sense a portion of it. The sensing capability of HRISs facilitates various network management functionalities, including channel estimation and localization. We discuss a hardware design for HRISs and detail a full-wave proof-of-concept. We highlight their distinctive properties in comparison to reflective RISs and active relays, and present a simulation study evaluating the HRIS capability for performing channel estimation. Future research challenges and opportunities arising from the concept of HRISs are presented.

[1]  Mehdi Bennis,et al.  Phase Configuration Learning in Wireless Networks with Multiple Reconfigurable Intelligent Surfaces , 2020, 2020 IEEE Globecom Workshops (GC Wkshps.

[2]  Shuguang Cui,et al.  Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis , 2019, IEEE Transactions on Wireless Communications.

[3]  Henk Wymeersch,et al.  Radio Localization and Mapping With Reconfigurable Intelligent Surfaces: Challenges, Opportunities, and Research Directions , 2020, IEEE Vehicular Technology Magazine.

[4]  Linglong Dai,et al.  Two-Timescale Channel Estimation for Reconfigurable Intelligent Surface Aided Wireless Communications , 2019, IEEE Transactions on Communications.

[5]  Ian F. Akyildiz,et al.  A New Wireless Communication Paradigm through Software-Controlled Metasurfaces , 2018, IEEE Communications Magazine.

[6]  Chau Yuen,et al.  Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication , 2018, IEEE Transactions on Wireless Communications.

[7]  David R. Smith,et al.  Microwave Imaging Using a Disordered Cavity with a Dynamically Tunable Impedance Surface , 2016 .

[8]  Mohamed-Slim Alouini,et al.  Smart radio environments empowered by reconfigurable AI meta-surfaces: an idea whose time has come , 2019, EURASIP Journal on Wireless Communications and Networking.

[9]  Emil Björnson,et al.  Intelligent Reflecting Surface Versus Decode-and-Forward: How Large Surfaces are Needed to Beat Relaying? , 2019, IEEE Wireless Communications Letters.

[10]  Truly Immersive,et al.  The Next Hyper Connected Experience for All. , 2020 .

[11]  Yonina C. Eldar,et al.  Dynamic Metasurface Antennas for 6G Extreme Massive MIMO Communications , 2020, IEEE Wireless Communications.

[12]  David R. Smith,et al.  Electronically steered metasurface antenna , 2021, Scientific Reports.

[13]  Alessio Zappone,et al.  Holographic MIMO Surfaces for 6G Wireless Networks: Opportunities, Challenges, and Trends , 2020, IEEE Wireless Communications.

[14]  Yonina C. Eldar,et al.  Dynamic Metasurface Antennas for Uplink Massive MIMO Systems , 2019, IEEE Transactions on Communications.

[15]  George C. Alexandropoulos,et al.  A Hardware Architecture For Reconfigurable Intelligent Surfaces with Minimal Active Elements for Explicit Channel Estimation , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).