Toward Intelligent Metasurfaces: The Progress from Globally Tunable Metasurfaces to Software‐Defined Metasurfaces with an Embedded Network of Controllers

Abstract

Metasurfaces, the ultrathin, 2D version of metamaterials, have recently attracted a surge of attention for their capability to manipulate electromagnetic waves. Recent advances in reconfigurable and programmable metasurfaces have greatly extended their scope and reach into practical applications. Such functional sheet materials can have enormous impact on imaging, communication, and sensing applications, serving as artificial skins that shape electromagnetic fields. Motivated by these opportunities, this progress report provides a review of the recent advances in tunable and reconfigurable metasurfaces, highlighting the current challenges and outlining directions for future research. To better trace the historical evolution of tunable metasurfaces, a classification into globally and locally tunable metasurfaces is first provided along with the different physical addressing mechanisms utilized. Subsequently, coding metasurfaces, a particular class of locally tunable metasurfaces in which each unit cell can acquire discrete response states, is surveyed, since it is naturally suited to programmatic control. Finally, a new research direction of software‐defined metasurfaces is described, which attempts to push metasurfaces toward unprecedented levels of functionality by harnessing the opportunities offered by their software interface as well as their inter‐ and intranetwork connectivity and establish them in real‐world applications.

Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces

“…The upper bound in Proposition 3 contains the product of the total channel gain ξ d,η,N between the source and IRS and the total channel gain ξ δ,ω,N between the IRS and the destination. This is the same structure as for the far-field SNR in (48), which has been analyzed in a series of previous works (e.g., [30]- [32], [43]). However, the near-field behavior has not be analytically studied with the same rigor.…”

“…An instructive way of interpreting the N 2 scaling can be found by factorizing the far-field SNR in (48) into two factors:…”

“…By setting the far-field approximation in (48), for an optimized IRS, equal to the mirror limit in (54), we obtain that is the largest array area that a mirror-mimicking IRS can make use of in this example. 9 This point is indicated by a square in Fig.…”

“…Depending on the IRS implementation, the phases and amplitudes might not be independently controllable but coupled[47]. Moreover, there are some implementations that allow for controlling the state of an element over a continuous range, while other implementations have a discrete number of possible states[48],[49]. To characterize the ultimate performance, we consider the ideal case when we can optimize the phases and amplitudes independently with arbitrary precision.…”

Split-cube-resonator-based metamaterials for polarization-selective asymmetric perfect absorption

“…At the same time, MSs help in minimizing Ohmic loss due to the short interaction volume. An abundance of interesting functionalities with such artificial sheet materials has been demonstrated at frequencies ranging from the microwave to the infrared and optical bands 6 – 8 . For example, MSs have been used to tailor the absorption and thermal emission properties 9 , 10 , manipulate the wavefront 11 , 12 , and engineer the dispersion of the induced phase 13 .…”