Stacked Intelligent Metasurface-Aided MIMO Transceiver Design

TL;DR

This paper introduces a novel transceiver architecture using stacked intelligent metasurfaces (SIM) that enhances wireless communication efficiency by enabling advanced wave manipulation and processing, reducing energy consumption and delay.

Contribution

The paper presents the design and potential advantages of SIM-based MIMO transceivers, including hardware architecture, application scenarios, and open research challenges.

Findings

SIM enables advanced electromagnetic wave processing.

Significant reduction in RF energy consumption.

Improved signal processing delay performance.

Abstract

Next-generation wireless networks are expected to utilize the 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 wave-based signal processing in wireless systems.