Stacked intelligent metasurfaces (SIM) provide a low-power means for MIMO transmission and reception using large multi-layer apertures that are digitally controlled. In this letter, we develop a SIM model that is consistent with metasurface theory. We use the Lorentzian function to emulate the amplitude-phase trade-off in meta-atoms. Therefore, realistic hardware impairments are introduced that change the system performance. Then, the general sheet transition conditions (GSTC) map the amplitude-phase trade-off to reflective and transmissive scattering parameters. Since the latter is only applicable to a single layer, we use network theory to extend it to multiple layers yielding an end-to-end SIM system model. Given the new feature, we derive a new Euclidean gradient of the system for optimization. Numerical results show that the ideal model overestimates sum rate by up to 7.5 bps/Hz at deeper configurations and that aperture size should be prioritized over cascade depth in physical SIM design.
Stacked intelligent metasurfaces (SIMs) enable near-field wavefront shaping via multiple programmable layers. However, widely used wave-domain models often neglect power scaling, mutual coupling, and geometric flexibility, while multiport-network formulations are physically consistent but computationally heavy and typi...
Yi-Nuo Dong, S. X. Ng, M. el-Hajjar· IEEE Transactions on Communi...· 0 citations
Wave-domain processing is an emerging paradigm in which signal-processing operations are partially shifted from the digital domain to the electromagnetic (EM) domain to reduce complexity, energy consumption, and latency in next-generation wireless systems. Stacked intelligent metasurfaces (SIMs) are a promising technol...
Stacked intelligent metasurfaces process the transmitted field layer by layer, and fluid antennas make the position of every radiator a design variable. Combined, they pack radiators at sub-wavelength spacings within and across layers, where mutual coupling governs the physics that current models omit. This paper devel...
Giovanni Iacovelli, Chandan Kumar Sheemar, S. Chatzinotas· 0 citations
Accurate nano-photonics simulations of large scale devices like optical metasurfaces require high accuracy reduced models for the device constituents. We present an automated framework for the optimization of Global Polarizability Matrix (GPM) models, which represent a complex scatterer as a small set of non-local effe...
This work presents a deep learning (DL)-assisted inverse-design framework for the automated synthesis of multifunctional pixelated metasurfaces. A deep neural network (DNN) is trained to map prescribed electromagnetic responses, specified by amplitude and phase, to corresponding 3-bit encoded unit-cell geometries for b...
M. Soltani, F. Ghorbani, S. Beyraghi et al.· Scientific Reports· 0 citations
Achieving multifunctional electromagnetic wave manipulation in full-space represents a long-standing scientific challenge. Conventional metasurfaces typically enable the manipulation of electromagnetic waves in the half-space and lack the capability to engineer multidirectional waves in full-space, resulting in low spa...
Su-Ying Li, Fan Ding, Yang Fu et al.· Journal of Optics· 0 citations
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