Stacked Intelligent Metasurface-Aided MIMO Transceiver Design

Stacked Intelligent Metasurface-Aided MIMO Transceiver Design

IEEE Wireless Communications

10.1109/MWC.013.2300259

https://doi.org/10.1109/mwc.013.2300259

Jiancheng An, Chau Yuen, Chao Xu, Hongbin Li, Derrick Wing Kwan Ng, Marco Di Renzo, Mérouane Debbah, Lajos Hanzo

30 April 2024

An, J., Yuen, C., Xu, C., Li, H., Ng, D. W. K., Di Renzo, M., Debbah, M., & Hanzo, L. (2024). Stacked Intelligent Metasurface-Aided MIMO Transceiver Design. IEEE Wireless Communications, 31(4), 123–131. https://doi.org/10.1109/mwc.013.2300259

Next-generation wireless networks are expected to utilize limited radio frequency (RF) resources more efficiently with the aid of intelligent transceivers. To this end, we propose a promising transceiver architecture relying on stacked intelligent metasurfaces (SIM). An SIM is constructed by stacking an array of programmable metasurface layers, where each layer consists of a massive number of low-cost passive meta-atoms that individually manipulate the electromagnetic (EM) waves. By appropriately configuring the passive meta-atoms, an SIM is capable of accomplishing advanced computation and signal processing tasks, such as multiple-input multiple-output (MIMO) precoding/ combining, multi-user interference mitigation, and radar sensing, as the EM wave propagates through the multiple layers of the metasurface, which effectively reduces both the RF-related energy consumption and processing delay. Inspired by this, we provide an overview of the SIM-aided MIMO transceiver design, which encompasses its hardware architecture and its potential benefits over state-of-the-art solutions. Furthermore, we discuss promising application scenarios and identify the open research challenges associated with the design of advanced SIM architectures for next-generation wireless networks. Finally, numerical results are provided for quantifying the benefits of wavebased signal processing in wireless systems.

Publisher Copyright

This research / project is supported by the Ministry of Education, Singapore - Academic Research Fund Tier 2
Grant Reference no. : MOE-T2EP50220-0019

This research is supported by core funding from: Science and Engineering Research Council of A*STAR (Agency for Science, Technology and Research) Singapore
Grant Reference no. : M22L1b0110

This research / project is supported by the National Science Foundation - NA
Grant Reference no. : ECCS-1923739, ECCS-2212940, CCF-2316865

This research / project is supported by the Australian Research Council’s Discovery Projects - NA
Grant Reference no. : DP210102169, DP230100603

This research / project is supported by the European Commission - H2020 ARIADNE project
Grant Reference no. : 871464

This research / project is supported by the European Commission - H2020 RISE-6G project
Grant Reference no. : 101017011

This research / project is supported by the Agence Nationale de la Recherche (France 2030, ANR PEPR Future Networks - NA
Grant Reference no. : NF-SYSTERA 22-PEFT- 0006

This research / project is supported by the Engineering and Physical Sciences Research Council - projects EP/W016605/1, EP/X01228X/1, EP/Y026721/1
Grant Reference no. : NA

This research / project is supported by the European Research Council’s Advanced Fellow Grant QuantCom - NA
Grant Reference no. : 789028

© 2024 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

https://oar.a-star.edu.sg/communities-collections/articles/21846

1536-1284
1558-0687

Institute of Microelectronics